Cone crusher control system and control method thereof

Abstract

The invention relates to the field of mine crushing control, in particular to a cone crusher control system and a control method thereof. The method comprises the following steps: acquiring multi-source data such as oil pressure, oil temperature and oil return state, and evaluating the health degree; starting judgment and switching time sequence control are executed, and switching parameters are generated; viscosity parameters are generated through oil temperature prediction and cold and heat coordinated regulation and control; generating an impact index based on load soft measurement and feeding control; carrying out liquid level oil return dual-channel coordination and abnormal grading treatment, and generating a reset sequence and a grading code; and finally, the control parameters are updated through remote diagnosis and parameter self-adaptive write-back. The equipment operation stability is improved, machine halt impact is prevented, and intelligent maintenance and efficient production are achieved.

Description

Technical Field

[0001] This invention relates to the field of mining crushing control, and in particular to a cone crusher control system and its control method. Background Technology

[0002] Cone crushers, as core equipment in the secondary or tertiary crushing stage of ore, rely on a main motor to drive an eccentric mechanism to achieve compression and layering crushing between the moving and fixed cones. These machines operate under long-term high loads, dust, and significant temperature fluctuations. The lubrication system forms an oil film to support the bearings and tooth surfaces and dissipates heat from the transmission pairs. The control system serializes the star-shaped start and delta-shaped operation of the main motor and maintains the stability of the crushing chamber through coordinated feeding and discharging. Existing control schemes mostly employ single-point threshold triggering based on pressure and oil temperature, and fixed-delay star-delta switching logic. They lack unified collection and standardized processing of oil return status, liquid level status, main motor electrical parameters, and environmental constraints. The release judgment and switching sequence are separated, easily leading to false starts and hard starts under conditions of insufficient lubrication pressure or abnormal oil temperature.

[0003] At the lubrication substation level, existing systems generally configure a main pump and a standby pump, but they rely on single-pump operation for extended periods, leaving the standby pump idle. There is a lack of quantitative scoring for health indicators such as start-stop counts, pressure rise time, and starting current phases, as well as a lack of rapid switching strategies triggered by abnormal pressure rise curves. This leads to frequent failure switching and pressure rise hysteresis issues during low-temperature, viscous phases. Temperature control typically employs decentralized control of heaters and coolers, lacking predictive scheduling for short-term operating condition fluctuations. In low-temperature, high-humidity environments, frost formation at the heat exchange end affects heat exchange capacity, the cooling duty cycle and fan airflow are not properly matched, resulting in low convergence efficiency of oil temperature within the target range. Furthermore, the impact of viscosity changes on oil pressure damping and friction loss is not explicitly modeled.

[0004] At the main circuit and starting circuit levels, the interlocking of star-delta contactor groups largely relies on hardware interlocking and fixed time intervals, lacking a self-checking mechanism for the timing consistency of drive signals and feedback signals. Contactor sticking, mis-closing, or switching hysteresis are difficult to identify in the field environment at the millisecond level, posing a risk of phase short circuits or reclosing. Alarm and reset procedures generally employ a unified shutdown and manual inspection approach, with inconsistent hierarchical strategies and guided reset steps. Parameters revert to factory default values ​​after reset, lacking a parameter adaptive write-back mechanism based on operational fingerprints.

[0005] At the level of operational condition perception and process scheduling, existing systems mostly use main motor current thresholds, belt weighing, or bin position signals to indirectly determine the load. They do not jointly model oil pressure fluctuations, power factor changes, and return oil status, making it difficult to reflect the real-time characteristics of "material layer thickness changes" and "ore inclusion degree." Anti-stagnation strategies mainly rely on empirical curves and lack closed-loop linkage with feed control and ore discharge control. Especially when oil temperature fluctuates across ranges, changes in oil viscosity cause the oil pressure-load mapping to drift. Single electrical parameter threshold triggering leads to misjudgments and delays, making it difficult to support unified configuration of linkage timing and yielding strategies.

[0006] In terms of the terminal layer and communication layer, the field wiring is complex and the visibility of the circuit status is limited. Remote diagnostics lacks sufficient granularity for online acquisition of the main circuit, control circuit and sensing circuit, and cannot provide structured fingerprints for fault reproduction and parameter optimization. Maintenance strategies mostly adopt calendar system or coarse-grained duration thresholds, and lack correlation with operational fingerprints such as start-stop times, star-delta switching time, oil pressure establishment time and overload occurrence rate. Summary of the Invention

[0007] This invention provides a control system and method for a cone crusher to solve the problems of how to perform load soft measurement and anti-lockdown coordinated load estimation based on standardized data and viscosity estimation parameters, generate load estimation parameters and use them for release judgment, star-shaped holding and angle switching, and linkage timing configuration and yielding strategy generation of feeding control and ore discharge control.

[0008] To address the aforementioned technical problems, this invention provides a control method for a cone crusher, comprising:

[0009] Multi-source observation and health characterization data are acquired, and sampling alignment, denoising, element extraction, and health calculation are performed to obtain a health score. The data includes oil pressure, oil temperature, oil return status, liquid level status, main motor current and voltage, power factor, contactor status, main pump and standby pump pressure boosting stage markings, and ambient temperature and humidity data.

[0010] Perform gated start-up and star-delta consistency release judgment, switchover timing configuration and execution, and switchover process consistency verification and evaluation to obtain switchover consistency identifier and switchover gap parameters;

[0011] The system acquires switching gap parameters, performs oil temperature prediction control and short-term prediction of cooling and heating synergy, scheduling of heating and compressor, and viscosity correction and defrosting determination, generating viscosity estimation parameters and defrosting indicators.

[0012] Based on viscosity estimation parameters, load soft measurement and anti-blocking machine coordinated load estimation are performed. The frequency band is identified by calculating the cross-spectral density and coherence coefficient of oil pressure and current. The feeding and discharge control adopts the model predictive control paradigm and configures the time series of the feed inverter frequency setting and the discharge port actuator stroke setting. The impact assessment process calculates the normalized cross-correlation peak value of the control sequence and the rate of change of load estimation parameters to generate the impact index parameter.

[0013] Perform consistency checks on the dual channels of liquid level return, consistency checks on graded yielding and guided reset, power limiting and frequency limiting control, and reset process configuration processing to generate a reset step sequence and anomaly classification code;

[0014] Based on the reset step sequence, anomaly classification code, and switching gap parameters, remote diagnosis and parameter adaptive write-back fingerprint accumulation, maintenance strategy generation, and write-back process processing are performed to update gating parameters, switching parameters, and yield parameters.

[0015] Furthermore, the process of acquiring multi-source observation and health characterization data, performing sampling alignment, denoising, feature extraction, and health score calculation to obtain a health score includes:

[0016] Acquire multi-source observation and health characterization data, perform sampling alignment and denoising processing to obtain standardized data;

[0017] Multi-source observation and health characterization elements are extracted from standardized data, and element extraction processing is performed to obtain element sequences.

[0018] The health status of the element sequence is calculated and processed to generate a health status score.

[0019] Furthermore, the process of performing gated start-up and star-delta consistency release judgment, handover timing configuration and execution, and handover process consistency verification and evaluation to obtain handover consistency identifiers and handover gap parameters includes:

[0020] Simultaneously read standardized data and health scores, perform gate activation and star-angle consistency release judgment processing, and obtain release instructions;

[0021] Based on the release command and standardized data, the handover timing is configured and executed to obtain the handover control sequence;

[0022] Based on the handover control sequence and standardized data, consistency verification and evaluation of the handover process are performed to obtain handover consistency identifiers and handover gap parameters.

[0023] Furthermore, the process of acquiring switching gap parameters, performing oil temperature prediction control and short-term prediction of cold and heat coordination, heating and compressor scheduling, and viscosity correction and defrosting determination, and generating viscosity estimation parameters and defrosting indicators includes:

[0024] Standardized data and switching gap parameters are acquired to perform oil temperature prediction control and short-term prediction of cold and heat synergy, and the prediction results are obtained.

[0025] Configure oil temperature prediction control and cooling-heating synergy duty cycle based on the prediction results, perform heating and compressor scheduling, and obtain thermal control commands;

[0026] The system performs oil temperature prediction control, cold and heat synergistic viscosity correction, and defrosting determination on thermal control commands, generating viscosity estimation parameters and defrosting indicators.

[0027] Furthermore, the process of generating the impact index parameters specifically includes:

[0028] Obtain standardized data and viscosity estimation parameters, perform load soft measurement and anti-stagnation combined load estimation to obtain load estimation parameters;

[0029] Configure the load soft measurement and anti-blocking machine coordination curve from the load estimation parameters, and perform feed control and ore discharge control to obtain the linkage control sequence;

[0030] The load soft measurement and anti-stagnation mechanism are used to conduct a coordinated impact assessment of the linkage control sequence, and impact index parameters are generated.

[0031] Furthermore, the process of performing consistency checks on the dual-channel return oil level, graded yielding and guided reset, power limiting and frequency limiting control, and reset procedure configuration processing to generate the reset step sequence and anomaly classification code specifically includes:

[0032] Acquire standardized data, thermal control commands, load estimation parameters, and switching consistency indicators; confirm the consistency of the dual-channel oil return and the consistency of graded yielding and guided reset to obtain consistency results.

[0033] Configure the consistency, graded yielding and guided reset yielding strategies for the dual-channel oil return of liquid level from the consistency results and impact index parameters, perform power limiting control and frequency limiting control, and obtain the abnormal grade code;

[0034] Configure the reset process for the abnormal classification code, including consistency of the liquid level return dual channel, graded concession, and guided reset, and generate a reset step sequence.

[0035] Furthermore, based on the reset step sequence, anomaly classification code, and switching gap parameters, the process of remote diagnosis and parameter adaptive write-back fingerprint accumulation, maintenance strategy generation, and write-back process processing, updating gating parameters, switching parameters, and yield parameters specifically includes:

[0036] Obtain the reset step sequence, abnormal classification code and switching gap parameters, perform remote diagnosis and parameter adaptive write-back fingerprint sedimentation to obtain fingerprint data;

[0037] Configure remote diagnostic and parameter adaptive write-back maintenance strategies from fingerprint data, generate rotation and window limit strategies, and obtain parameter update sets;

[0038] The parameter update set is used in the remote diagnostics and parameter adaptive write-back process to update the gating parameters, switching parameters, and yield parameters.

[0039] Furthermore, the load estimation steps involving soft measurement and anti-sluggish operation include:

[0040] Establish a time window corresponding to the current crushing cycle, and align the recent data of main motor current and power factor with the oil pressure sequence and return oil status sequence based on the most recent release record and switching record;

[0041] The pressure fluctuations corresponding to the rising current of the main motor in the oil pressure timing sequence are segmented to distinguish between stable segments and abrupt segments. The pressure fluctuations are then confirmed by combining the oil return state sequence to determine whether they are triggered by changes in oil circuit damping.

[0042] Furthermore, the process of load soft measurement and anti-sluggish machine coordinated load estimation also includes:

[0043] The coupling segment between electromagnetic side load and mechanical side load is identified to infer the degree of ore inclusion in the crushing chamber;

[0044] The correspondence between the multi-point sampling sequence of inlet and outlet oil temperatures and the viscosity estimation parameters is read, and the rheological characteristics of different temperature zones are mapped into corrections for oil pressure damping and bearing friction, so as to eliminate estimation deviations under the same operating conditions in cold and hot oil.

[0045] Furthermore, a cone crusher control system, applied to the method described in any of the above embodiments, includes:

[0046] The health score module is used to acquire multi-source observation and health characterization data, perform sampling alignment, denoising, feature extraction and health score calculation to obtain a health score;

[0047] The switching control module is used to perform gate start-up and star-delta consistency release judgment, switching timing configuration and execution, and switching process consistency verification and evaluation processing to obtain switching consistency identifier and switching gap parameters;

[0048] The oil temperature and viscosity control module is used to acquire switching gap parameters, perform oil temperature prediction control and short-term prediction of cold and heat coordination, heating and compressor scheduling, as well as viscosity correction and defrosting judgment processing, and generate viscosity estimation parameters and defrosting indicators.

[0049] The load estimation and control module is used to perform load soft measurement and anti-blocking machine coordinated load estimation based on viscosity estimation parameters. It identifies the frequency band by calculating the cross-spectral density and coherence coefficient of oil pressure and current. The feeding and discharge control adopts the model predictive control paradigm and configures the time series of the feed inverter frequency setting and the discharge port actuator stroke setting. The impact assessment processing calculates the normalized cross-correlation peak value of the control sequence and the rate of change of the load estimation parameters to generate the impact index parameter.

[0050] The anomaly handling module is used to perform consistency verification of the dual channels of liquid level return, consistency verification of graded yielding and guided reset, power limiting and frequency limiting control, and reset process configuration processing, generating a reset step sequence and anomaly classification code;

[0051] The remote diagnostics and maintenance module is used to perform remote diagnostics, parameter adaptive write-back fingerprinting, maintenance strategy generation, and write-back process processing based on reset step sequence, anomaly classification code, and switching gap parameters, and to update gating parameters, switching parameters, and yield parameters.

[0052] The key innovations of this invention include:

[0053] (1) Based on dual thresholds of oil pressure and oil temperature, gate release is jointly arranged with the timing interlocking and consistency self-check of star and delta switching. This innovation corresponds to the beneficial effect of consistent data input and gate release being driven by the same source. Release, switching and self-check are no longer separated, and the switching gap parameter and switching consistency identifier run through the entire startup process.

[0054] (2) Integrated cooling and heating oil temperature prediction scheduling and viscosity estimation into the chain. The thermal control command and viscosity estimation parameters are output synchronously and used as a pre-correction term for load soft measurement, supporting consistent load mapping across temperature zones and bringing the beneficial effect of cooling and heating synergy feedforward to load estimation.

[0055] (3) Structured output format for load soft measurement and anti-blocking machine coordination. The output is load estimation parameters rather than single-point thresholds, including load amplitude items, material layer trend items, and ore inclusion risk items, which directly drive the linkage timing configuration and yield strategy generation of feed control and ore discharge control, forming beneficial effects on the process side.

[0056] The following are its main beneficial effects:

[0057] (1) Through the collection, alignment, and denoising of multi-source observation and health characterization, standardized data and element sequences with unified time reference, unified dimensions, and unified semantics are formed, providing input from the same source for subsequent release judgment, cold and hot coordination, load soft measurement, and linkage control. This processing eliminates sampling drift and noise deviation between oil pressure, inlet and outlet oil temperature, return oil and liquid level status, main motor electrical parameters, contactor status, pump group pressurization stage, and environmental information. Subsequent modules directly use this data set for judgment and scheduling, reducing the interference of manual experience thresholds on process stability.

[0058] (2) The release decision directly uses standardized data and health scores. The star-shaped holding and delta-shaped switching sequences are derived from the release results, and switching gap parameters and switching consistency indicators are introduced for timing interlocking and self-checking. This approach makes lubrication pressure compliance, oil temperature window achievement, emergency stop and overload self-checking, and phase loss detection a unified entry point. The release signal and switching control are generated in the same time context, and the interlocking status of the main circuit and control circuit is updated synchronously, reducing the risk of false start and hard start.

[0059] (3) The thermal control command generated by the oil temperature prediction control forms a duty cycle coordination between the compressor and the heater, and outputs viscosity estimation parameters and defrost indicators at the same time. The viscosity estimation parameters enter the load soft measurement process to correct the influence of oil rheological differences caused by temperature range changes on oil pressure damping and bearing friction, so that the same operating condition can obtain a consistent load mapping under cold oil and hot oil conditions, and reduce load estimation deviation. Attached Figure Description

[0060] Figure 1 A schematic flowchart of a cone crusher control method provided in an embodiment of this application;

[0061] Figure 2 A structural block diagram of a cone crusher control system provided in an embodiment of this application;

[0062] Figure 3 An overall electrical schematic diagram of a cone crusher control system provided in this application embodiment;

[0063] Figure 4 A schematic diagram of the core control loop of a cone crusher control system provided in this application embodiment;

[0064] Figure 5 A schematic diagram of the manual and automatic control interface of a cone crusher control system provided in an embodiment of this application;

[0065] Figure 6 A schematic diagram of a cone crusher control system for temperature monitoring and safety interlock protection provided in an embodiment of this application;

[0066] Figure 7A wiring diagram of a cone crusher control system assembly is provided for an embodiment of this application;

[0067] Figure 8 This application provides an embodiment of an input / output (I / O) interface definition and power distribution wiring diagram for a cone crusher control system. Detailed Implementation

[0068] Example 1: Refer to Figure 1 This is a flowchart illustrating a cone crusher control method provided in an embodiment of the present invention. The process may include at least steps S100-S600:

[0069] S100. Acquire multi-source observation and health characterization data, perform sampling alignment, noise reduction, element extraction and health calculation processing to obtain a health score; the data includes oil pressure, oil temperature, return oil status, liquid level status, main motor current and voltage, power factor, contactor status, main pump and standby pump pressure boosting stage markings and ambient temperature and humidity data.

[0070] S200, executes gate start-up and star-delta consistency release judgment, switchover timing configuration and execution, and switchover process consistency verification and evaluation processing to obtain switchover consistency identifier and switchover gap parameters;

[0071] S300: Obtain switching gap parameters, perform oil temperature prediction control and short-term prediction of cold and heat coordination, heating and compressor scheduling, viscosity correction and defrosting judgment processing, and generate viscosity estimation parameters and defrosting indicators.

[0072] S400, based on viscosity estimation parameters, performs load soft measurement and anti-blocking machine coordinated load estimation, feed and discharge control, and impact assessment processing to generate impact index parameters;

[0073] S500 performs consistency checks on the dual channels of liquid level return, graded yielding and guided reset, power limiting and frequency limiting control, and reset process configuration processing, generating a reset step sequence and anomaly classification code.

[0074] S600 performs remote diagnostics and parameter adaptive write-back fingerprinting, maintenance strategy generation, and write-back process processing based on reset step sequence, abnormal classification code, and switching gap parameters, updating gate control parameters, switching parameters, and yield parameters.

[0075] Step S100 includes at least steps S110-S130:

[0076] S110. Acquire multi-source observation and health characterization data, perform sampling alignment and denoising processing to obtain standardized data;

[0077] Acquire multi-source observation and health characterization data, including oil pressure, oil temperature, return oil status, liquid level status, main motor current and voltage, power factor, contactor status, main pump and standby pump boosting stage markers, and ambient temperature and humidity data. Specifically, firstly, establish a data acquisition link between the control cabinet and the sensing layer. This data acquisition link simultaneously covers the oil pressure sensor, oil temperature sensor, return oil switch, liquid level relay, main motor current and voltage sampling module, power factor acquisition module, status feedback loops of main contactor, star contactor, and delta contactor, starting current and boosting process monitoring loops of main pump and standby pump, and ambient temperature and humidity detection unit. Specifically, multiple temperature detectors, including temperature detectors T1 to T6, are installed in the inlet and return oil lines of the lubrication system to generate time-series curves of inlet and return oil temperatures; an oil pressure sensor is configured in the main oil line to generate an oil pressure time-series curve; a return oil switch is installed in the return oil path to form a dual-channel state sequence with the level relay; on the electrical side, current transformers and voltage sampling modules are used to generate time-series data of the main motor phase current and line voltage, while a power factor acquisition module is used to generate power factor time-series data; on the execution side, the engagement and release state sequences of the main contactor, star contactor, and delta contactor are collected to record the actual timing of star holding and delta switching; on the lubrication subsystem side, the starting current trajectory and pressure rise time of the main pump and standby pump after power-on are collected to support subsequent health characterization.

[0078] The multi-source observation and health characterization data are simultaneously processed into sampling alignment and denoising after acquisition. Specifically, the timestamps of the data from each channel are first uniformly processed, and a master clock is established according to the unified sampling period on site. Early and late samples are incorporated into the master clock through interpolation and repetition filling. Missing samples are set up with missing bitmaps and filled or removed using neighborhood smoothing and median judgment without changing the original trend. Then, band-limited filtering and pulse interference suppression are performed on continuous quantities such as oil pressure, oil temperature, and current. Jitter elimination, glitch merging, and bounce suppression are performed on binary quantities such as contactor status, return oil, and liquid level. The pressurization sections of the main pump and standby pump are identified, and the starting point, inflection point, and stable point are marked for direct reference in subsequent element extraction. After the above alignment and noise reduction processing is completed, the dimensions and ranges are further standardized: continuous quantities such as oil pressure, oil temperature, main motor current, main motor voltage, power factor, and boost time are uniformly converted into standard scales under engineering dimensions, and discrete quantities such as contactor status, return oil switch, and level relay are uniformly encoded into consistent status flags, and the valid value set of the status flags is registered.

[0079] Standardized data is generated, including oil pressure timing, oil temperature timing, oil return status sequence, liquid level status sequence, main motor current and voltage timing, power factor timing, contactor status sequence, main pump and standby pump pressure boosting stage markers and starting current trajectories, as well as ambient temperature and humidity sequences, all processed with a unified master clock and unified dimensions. This standardized data is uniformly stored in the data channel and includes a time window index to ensure seamless referencing in subsequent windowed processing steps.

[0080] S120. Extract multi-source observation and health characterization elements from the standardized data, perform element extraction processing, and obtain an element sequence.

[0081] The standardized data is read and segmented according to fixed-length time windows. Within each time window, elements related to health characteristics are extracted. Specifically, for the oil pressure time sequence, the pressure rise rate, pressure stability amplitude, and pressure fluctuation are extracted within the pressure rise segment. These quantities are then bound to the segment markers of the main pump or standby pump to form oil pressure elements corresponding one-to-one with pump operating conditions. For the oil temperature time sequence, the temperature difference between the inlet and outlet oil, the outlet oil temperature gradient, and the mean value within the window are extracted based on the spatial arrangement relationship from T1 to T6, and it is recorded whether the oil temperature is within the preset oil temperature window. For the main motor current and voltage time sequence, the phase current amplitude, phase current imbalance, time average value of the power factor, and fluctuation amplitude are extracted. The contactor state sequence is divided into a star-shaped holding segment and a delta-shaped operating segment at the marker, and the statistical values ​​of electrical parameters within each segment and the amplitude of inter-segment jumps are recorded. Time window consistency statistics are performed on the outlet oil state sequence and the liquid level state sequence to obtain the outlet oil flow indicator and the normal liquid level indicator. Interval averaging and fluctuation calculations are performed on the ambient temperature and humidity to provide a reference context for the temperature control strategy.

[0082] Furthermore, at the level related to health characterization, the boost time, peak starting current, and starting current decay rate are calculated for the main pump and the standby pump respectively, thereby forming health characterization elements related to the pump status; for the contactor state sequence of star holding and delta switching, the star holding duration, delta switching delay, and switching gap are statistically analyzed, and these switching elements are aligned and registered with the main motor current, oil pressure, and oil temperature elements in the corresponding time period; for the dual-channel status of return oil and liquid level, the number of concurrent consistency events and the duration of inconsistency within the time window are statistically analyzed to support the threshold comparison of inconsistency duration in subsequent consistency confirmation.

[0083] Once all the above elements are generated within each time window, they are arranged in chronological order to form an element sequence. The element sequence includes oil pressure elements, oil temperature elements, electrical parameter elements, contactor switching elements, dual-channel elements for oil return and liquid level, pump pressurization elements, and ambient temperature and humidity elements. Segment indexes and equipment role indexes are established in the data structure to ensure that elements between different devices and different segments within the same time window can be accurately associated and called by downstream steps.

[0084] S130. Perform health calculation processing on the element sequence to generate a health score;

[0085] Read the element sequence and establish health calculation channels according to equipment role and paragraph type, including health calculation channels for main pump and standby pump, switching health calculation channels for star-shaped holding and angle switching, and operation health calculation channels for lubrication, oil return and liquid level. Specifically, within the pump health calculation channel, based on factors such as the pressure rise time, peak starting current, and starting current decay rate within each time window, combined with the oil pressure stability amplitude and pressure fluctuation within that time window, a consistency judgment of the pump's pressure rise and stabilization capabilities is established and accumulated in chronological order. Within the switching health calculation channel, based on the star connection holding time, delta switching delay, and switching gap, combined with the main motor phase current imbalance and inter-segment jump amplitude within that segment, a consistency judgment of the switching process is established and accumulated in segment sequence. Within the lubrication, return oil, and level operation health calculation channel, based on the concurrent consistency count and inconsistency duration of the return oil unobstructed indicator and the normal level indicator within the time window, combined with whether the oil temperature is within the oil temperature window and the statistics of the return oil temperature gradient and the average value within the window, a judgment of the lubrication, return oil, and level operation status is established and accumulated in chronological order.

[0086] To ensure the comparability of health status calculations across different equipment roles and segments, the dimensional differences of the elements are re-standardized in the processing of the three channels, and a unified score domain is established. For elements related to equipment lifespan, such as long-term drift in boost time, long-term increase in peak starting current, long-term shortening of star-shaped holding time, and long-term increase in angle switching delay, a time series slow-varying tracker and a steady-state window are set to ensure that long-term changes are reflected within the statistical scope. For elements related to instantaneous consistency, such as occasional anomalies in switching gaps and instantaneous events of inconsistency between return oil and liquid level, short-term windows are set to capture instantaneous deviations, and the results are merged and registered with the long-term slow-varying tracker results within the same score domain. After the above merging, a health status score is generated, which consists of pump health status score, switching health status score, and lubrication, return oil, and liquid level operation health status score. The data structure retains equipment role indexes and segment indexes to support differentiated use by different roles in subsequent steps.

[0087] After the health score calculation is completed, the health score is bound to the key identifier in the element sequence and registered in the health characterization data channel. To ensure seamless transitions between steps, explicit references are established during registration: First, the health score is provided to S210, enabling the gated start-up and star-angle consistency release judgment to read the score within the corresponding time window, used to correct the configuration of the release threshold and pre-lubrication duration; Second, the health score is provided to S220, enabling the gated start-up and star-angle consistency switching sequence to configure the switching delay and switching gap based on the pump health score and switching health score when performing star-shaped holding and angle-shaped switching control; Third, the health score is provided to S620, enabling the remote diagnosis and parameter adaptive write-back to reference the time series of pump health score and switching health score when generating the rotation strategy and window limit strategy; Fourth, the health score is associated with the time window index of the standardized data, facilitating S310 and S330. When performing oil temperature prediction control, short-term prediction of cold and heat coordination, viscosity correction and defrosting determination, windows related to health characterization are consistently referenced; fifth, the health score is associated with the segment index of the element sequence, so that S410 can call the pump boosting element and switching element as context constraints when performing load soft measurement and anti-stagnation coordinated load estimation.

[0088] Step S200 includes at least steps S210-S230:

[0089] S210: Synchronously read standardized data and health score, perform gate start-up and star-angle consistency release judgment processing, and obtain release command;

[0090] The control system first synchronously reads the standardized data and the health score from the data channel. The standardized data is a data set formed after sampling alignment, noise reduction, and dimension unification, specifically including oil pressure timing, oil temperature timing, return oil state sequence, liquid level state sequence, main motor current and voltage timing, power factor timing, state sequence of main contactor, star contactor, and delta contactor, main pump and standby pump pressure boosting stage markers and starting current trajectories, and ambient temperature and humidity sequence. The health score consists of pump health score, switching health score, and lubrication, return oil, and liquid level operation health score, and establishes a one-to-one binding relationship with the standardized data through time window index and equipment role index. After the system completes the synchronization of the above two types of inputs, it enters the gated start-up and star-delta consistency release judgment process.

[0091] Specifically, following the principle of lubrication first, the system performs segment identification on the oil pressure timing sequence and return oil status sequence in the standardized data to confirm whether there are pressure reach indicators and return oil unobstructed indicators within the current time window. If no pressure reach indicator appears, the system maintains the pre-lubrication state and records the reason for the absence for subsequent fingerprinting entries in S610. When it is confirmed that a pressure reach indicator has appeared and the return oil unobstructed indicator is established, the system continues to perform window checks on the oil temperature timing sequence and the ambient temperature and humidity sequence to determine whether the oil temperature is within the oil temperature window. Understandably, the initial upper and lower limits of the oil temperature window are jointly determined by the equipment setting value and the model library setting value. The lubrication, return oil, and liquid level operation health scores in the health score are used to fine-tune the upper and lower limits of this window to ensure that the window is consistent with the current oil viscosity state and ambient temperature and humidity.

[0092] After lubrication and oil temperature conditions are met, the system reads the pump health score and switching health score from the health rating. Specifically, the system adjusts the pre-lubrication duration and the priority selection strategy for the main pump or standby pump based on the pump health score. When the pump health score is below the threshold, the system prioritizes the pump with the higher score as the current working pump and extends the pre-lubrication duration accordingly. When the scores of both pumps are close, the system selects the working pump according to the rotation strategy and adds a rotation mark to the release judgment record so that S620 can directly reference it when generating the rotation strategy and window limit strategy. Within the same time window, the system simultaneously reads the switching health score to obtain the consistency of historical star-shaped maintenance and angle-shaped switching. If the switching health score shows a recent trend of switching gap deviation, the system registers a "switching adjustment suggestion" during the release judgment, which is used by S220 to correct the initial value when configuring the switching sequence.

[0093] The system further performs a zero-point self-check on the state sequences of the main contactor, star contactor, and delta contactor in the standardized data to confirm that there is no residual engagement or adhesion; simultaneously, it checks that the emergency stop, overload, and phase loss monitoring values ​​are within the allowable range. These checks are completed within the same time window and written into the release decision record. When all gating conditions are met, the system generates a release command. The release command is output in the form of a structured parameter set, including at least a release flag, remaining pre-lubrication time, initial star hold value, initial delta switch value, and switching adjustment suggestions. To maintain consistency, the release command is immediately pushed to the timing configuration channel of S220 after generation and referenced in S310 as part of the context of oil temperature predictive control and short-term cold / hot coordinated prediction, ensuring that subsequent control maintains a consistent understanding of the switching transient. Simultaneously, the system records key timestamps and criteria entries from the release decision process to the data channel for fingerprinting in S610.

[0094] S220. Based on the release command and standardized data, perform handover timing configuration and execution processing to obtain the handover control sequence;

[0095] The control system receives and parses the release command. First, it reads the release flag to determine whether entry into the switching timing configuration process is permitted. If the release flag is permitted, the system determines whether pre-lubrication has been completed based on the remaining pre-lubrication time in the release command. If not, the system maintains the lubrication subsystem operation until the remaining time is cleared, and triggers the switching timing configuration at the clearing time. If completed, it directly enters the timing configuration process at the current moment. While parsing the initial values ​​for star-shaped hold and delta-shaped switching, the system simultaneously reads the "switching adjustment suggestion," using this suggestion as a fine-tuning amount for the initial values. The adjustment result is recorded as the baseline value of the timing parameters for this cycle in the timing buffer for consistency comparison during subsequent execution.

[0096] The system generates a draft switching timing sequence based on the timing parameter baseline values. The draft, presented in timeline form, outlines the start and end times of the star-hold phase, the start time of the delta-switching phase, and the engagement and release arrangements of the main contactor. After the draft is generated, the system performs a linkage initialization test on the state sequences of the main contactor, star contactor, and delta contactor in the standardized data: the system tentatively drives the star contactor coil with a short duty cycle and collects changes in circuit electrical parameters to confirm that the coil and feedback contacts are working properly; the main contactor and delta contactor are tested in the same way to ensure consistency between state feedback and drive relationship. After successful testing, the system formally issues star-holding and delta-switching control commands, writes the time stamps from the draft into the control task queue, and binds the event trigger conditions.

[0097] During the star-connection holding phase, the system drives the main contactor to engage with the star contactor, and continuously reads the main motor current and voltage timing, power factor timing, and oil pressure timing from the standardized data throughout the holding phase to form the transient curve for this phase. The system performs real-time boundary monitoring on the transient curve. Once the main motor current surges above the preset upper limit, the system adjusts the buffer amount of the delta switching initial value without changing the end time of the star-connection holding, so as to complete the buffer preparation before the subsequent switching opportunity arrives. At the same time, the system continuously monitors the emergency stop, overload, and phase loss monitoring values. When any monitoring value becomes unallowed, the system immediately freezes the switching task queue and maintains the star-connection holding until the upper interlock is released and the pre-lubrication conditions are still valid, and then S210 regenerates a new release command.

[0098] When the star-connection holding end time specified in the draft is reached, the system executes the star-connection release operation and enters the delta-connection switching preparation phase. During the preparation phase, the system confirms that the star contactor is fully released, the main contactor remains engaged, and the delta contactor is in standby mode. The system reads the contactor state sequence from the standardized data using a query method to confirm the release time point, and observes and records the main motor current and oil pressure during the interval between release and engagement for consistency self-checking of S230. Further, the system triggers the delta contactor to engage at the delta-connection switching start time specified in the draft, and continues to collect contactor state and electrical parameter changes, forming the execution trajectory of the delta-connection switching phase. The system summarizes the drive commands and collected data from the star-connection holding phase and the delta-connection switching phase in chronological order, generating a structured switching control sequence, and writes this switching control sequence as output into the data channel; simultaneously, the baseline values ​​of the timing parameters for this cycle and the trial verification results are also archived.

[0099] S230. Based on the handover control sequence and standardized data, perform handover process consistency verification and evaluation to obtain handover consistency identifier and handover gap parameters;

[0100] The control system reads the switching control sequence from the data channel, reading the drive commands and corresponding sampled data for the star-holding phase and the delta-switching phase one by one, and calling the contactor state sequence, electrical parameter timing sequence, oil pressure timing sequence, return oil state sequence, and liquid level state sequence from the standardized data for comparison. The system first performs an integrity check on the star-holding phase, confirming that the status flags of the main contactor and the star contactor correspond one-to-one with the drive commands throughout the entire time period from the start to the end of the phase, and that there are no unauthorized state flips; if a flip exists, the system immediately marks "phase inconsistency" in the self-test record of this cycle, terminates the consistency determination of this cycle, and binds the mark to the release determination number of the current period, so that S610 can reproduce the event chain when fingerprinting.

[0101] After the star-shaped holding phase verification is passed, the system enters the switching gap identification process. The system uses the star-shaped release time as the gap start point and the delta-shaped engagement time as the gap end point. Within the gap cycle, it reads the minimum, average, and trend values ​​of the main motor current and oil pressure, and compares them with the timing parameter baseline values ​​in the release command record to confirm whether the gap cycle is within the allowable range. When the gap cycle is within the allowable range, the system registers the gap cycle as the switching gap parameter for this cycle; when the gap cycle deviates from the allowable range, the system still registers it as a switching gap parameter, but adds a "deviation mark" during the consistency identifier construction to prompt S310 to set a short-time compensation ratio in the thermal control command.

[0102] The system performs a consistency check on the execution trajectory during the angle switching phase, confirming that the angle contactor engages at the predetermined time and that the main motor current gradually converges to the angle operating range during the short transition period. Simultaneously, the system checks that no unacceptable states occur during the emergency stop, overload, and phase loss monitoring parameters during the switching phase. The system further reads the oil return status sequence and the liquid level status sequence to verify that no persistent inconsistencies occur during the switching phase. If the above checks pass, the system constructs a switching consistency identifier indicating a compliant state; if any item fails, the system constructs a switching consistency identifier indicating a non-compliant state and includes a non-compliant source entry in the record, including sources such as phase inconsistency, gap deviation, emergency stop triggering, overload triggering, phase loss triggering, and inconsistencies between oil return and liquid level. The system writes the switching consistency identifier and switching gap parameters as outputs of this step into the data channel, and archives the key timestamps of the switching control sequence for this cycle, the sampling summary of electrical parameters and oil pressure within the gap cycle, and non-compliant source entries (if any), for read by S310, S510, S610, and S620.

[0103] Step S300 includes at least steps S310-S330:

[0104] S310. Obtain the standardized data and the switching gap parameter, perform oil temperature prediction control and short-time prediction of cold and heat synergy, and obtain the prediction result;

[0105] The control system synchronously reads the standardized data and the switching gap parameters via the data bus. The standardized data includes multi-point sampling sequences of inlet and outlet oil temperatures, oil pressure timing, return oil status sequence, liquid level status sequence, main motor current and voltage timing, power factor timing, status sequences of main contactors, star contactors, and delta contactors, main pump and standby pump boosting stage markers and starting current trajectories, and ambient temperature and humidity sequences, all obtained after sampling alignment and noise reduction. The switching gap parameters are output by S230, recording the actual gap period and deviation mark between star release and delta engagement. The system first establishes a time window corresponding to the current operating cycle, and starting from the gate start release record, aligns the key timestamps of star hold and delta switching with the multi-point sampling sequences of inlet and outlet oil temperatures, calibrating the changes in temperature, oil pressure, and electrical parameters within several sampling cycles before and after the switch, so that short-term predictions are corrected at the actual location of the switching disturbance. Specifically, the system converts the switching gap parameter into a "transient disturbance identifier," which indicates the short-term impact range on the oil circuit temperature field and return oil viscosity at the moment of switching. When the switching gap parameter has a deviation symbol, the system introduces a higher disturbance weight in the short-term prediction and attaches a "disturbance compensation suggestion" to the prediction output to guide subsequent scheduling.

[0106] After establishing the time window and disturbance flags, the system enters the oil temperature predictive control and short-term prediction of combined cooling and heating. The system reads the near-end and far-end measuring points in the multi-point sampling sequence of inlet and outlet oil temperatures, calculates the time series difference and gradient trend of each measuring point, and estimates the available heat exchange capacity on the heat exchange side in conjunction with the ambient temperature and humidity sequence. The system reads the oil pressure time sequence and outlet oil status sequence to identify whether the oil circuit is in a state of sufficient flow and unobstructed outlet oil flow, in order to determine whether the heat exchange distribution path in the oil circuit is complete. The system simultaneously reads the short-term average value and fluctuation amplitude of the main motor current and power factor, establishes the short-term load level interval judgment, and cross-compares it with the star-hold and delta switching state sequences to identify whether there is an oil temperature rise or fall trend caused by load changes within the prediction interval. The above-mentioned multi-source elements of temperature, flow rate, heat exchange, and load are uniformly organized into a short-term prediction input set in this step. The prediction process advances forward on the time window in a rolling manner. Each time a sampling cycle is advanced, a set of real-time temperature trends, outlet oil viscosity trends, and heat demand trends are generated. To maintain consistency with previous health characterization, the system uses the lubrication, oil return, and liquid level operation health scores from the previous health rating as weighting adjustment factors during the process. When the score indicates that the recent operation has fluctuated significantly, a stability flag is added to the trend output of this step to prompt subsequent scheduling to limit the rate of change in duty cycle configuration.

[0107] After short-term prediction is completed, the system generates a "prediction result". The prediction result is output in the form of a structured set, including at least: a temperature trend entry, which gives the time-series trend of inlet and outlet oil temperatures, temperature difference changes, and possible interval boundaries within the prediction time window; a heat demand entry, which gives suggestions on the allocation of heat load and cold load to be borne by heaters and compressors within the same time window, and indicates the proportion interval matching the current load level; a disturbance compensation entry, which gives the compensation segment and suggested compensation intensity within the time window for transient disturbances caused by the switching gap parameters; and a heat exchange availability entry, which gives the upper limit of available heat exchange capacity and fan speed reference based on ambient temperature and humidity estimation. The system writes the prediction result into the data channel as the sole input for configuring duty cycle and executing scheduling in S320; at the same time, it writes the reference key of the disturbance compensation entry into the self-test record of S230, so that a round-trip reference is formed between the switching self-test and the heat prediction; in addition, the system writes the interval boundaries in the temperature trend entry into the upstream reference of S410 to ensure that a consistent temperature window context is obtained during load soft measurement.

[0108] S320. Configure the oil temperature prediction control and the cold and heat coordinated duty cycle from the prediction results, perform heating and compressor scheduling, and obtain thermal control commands;

[0109] The control system reads and analyzes the prediction results, and performs comprehensive duty cycle configuration and equipment-level scheduling based on temperature trend entries, heat demand entries, disturbance compensation entries, and heat exchange availability entries. The system establishes a "duty cycle configuration baseline" for the current cycle, using the proposed distribution of heat and cooling loads as initial values. Then, based on the heat exchange availability entries, it limits the capacity of the cold source side to avoid excessive cooling when the ambient temperature is low or the air humidity is high. Furthermore, the system reads the disturbance compensation entries; if the marked compensation segment overlaps with the current cycle, it temporarily increases the heater-side proportion or increases the fan speed within that segment to offset short-term oil temperature fluctuations caused by switching transients. After completing the baseline and compensation overlay, the system enters the execution layer scheduling generation stage.

[0110] Specifically, the system represents heater output using a power percentage range, compressor operation using a duty cycle range, and fan operation using a speed percentage range, generating a dispatchable scheduling sequence. To ensure execution layer stability, the system sets minimum start-stop intervals and minimum hold times for all execution quantities to avoid frequent start-stops; it sets a phase-staggered strategy for the linkage between the fan and compressor, ensuring that airflow changes occur before the compressor duty cycle increases, thereby improving heat exchanger availability; it sets a mutual exclusion window for the competition between the heater and compressor, prioritizing the compressor's need to maintain oil temperature within the upper limit when both sides' power demands exceed the set value, and compensating for the heater's increase in the next sampling period. During the execution of the above scheduling logic, the system continuously reads the oil pressure timing and return oil status sequence from the standardized data. If poor return oil flow or abnormal liquid level is detected in any sampling period, the system immediately reduces the compressor duty cycle and maintains a moderate speed on the fan side to alleviate the instantaneous burden on the oil circuit on the heat exchanger side; simultaneously, this criterion is written to the exception buffer for S510 to reference during consistency confirmation.

[0111] After completing the duty cycle configuration and equipment scheduling, the system generates a "thermal control command". This thermal control command is output as a periodic, structured sequence, and includes at least the heater power percentage curve, compressor duty cycle curve, fan speed curve, and temporary correction rules within the disturbance compensation zone; it also includes safety-related constraints, including minimum start-stop interval, minimum hold time, and mutual exclusion window parameters. The system writes the thermal control command into the data channel as direct input for viscosity correction and defrosting determination in S330; and synchronously registers the command in the input list of S510, ensuring that subsequent consistency confirmation of the dual-channel oil return and the consistency confirmation of graded yielding and guided reset reuse the same control sequence; simultaneously, the duty cycle configuration benchmark and execution layer scheduling results for this cycle are written into the fingerprint record of S610 for use in parameter update set construction and comparison during remote diagnostics and parameter adaptive write-back.

[0112] S330. Perform oil temperature prediction control, cold and heat synergistic viscosity correction, and defrost determination on the thermal control command to generate viscosity estimation parameters and defrost identifier;

[0113] The control system reads the multi-point sampling sequence of inlet and outlet oil temperatures, the return oil state sequence, and the ambient temperature and humidity sequence from the thermal control commands and standardized data. During the periodic execution of the thermal control commands, it performs online estimation and judgment of oil viscosity and heat exchange side frosting state. First, within the matching range of the heater power percentage curve and the compressor duty cycle curve, the system tracks the response speed, average value of the stable segment, and short-term fluctuations of the multi-point sampling sequence of inlet and outlet oil temperatures, and compares it with the response of the previous period to identify the rheological characteristics of the oil in the current temperature range. The system cross-validates these rheological characteristics with the unobstructed status indicators of the return oil state sequence. If the return oil state is repeatedly obstructed and the oil temperature response speed is low within the same temperature range, the oil is determined to have high viscosity characteristics in this range, requiring an increase in the bias of the heater proportion during viscosity correction. If the oil temperature response speed is high and the return oil state is stable within the same temperature range, the oil is determined to have low or medium viscosity characteristics in this range, allowing for a reduction in the heater-side bias or a moderate increase in the compressor-side proportion in subsequent cycles. The system converts the above-mentioned determination of the rheological properties of oil into "viscosity estimation parameters". These parameters are represented in intervals, corresponding one-to-one with the temperature intervals within the current cycle, and are accompanied by applicable priority markers so that S410 can call them when performing load soft measurement and anti-stagnation engine coordinated load estimation.

[0114] The system enters the defrosting judgment process. The system reads the correspondence between the ambient temperature and humidity sequence and the fan speed curve and compressor duty cycle curve, focusing on the section where the compressor duty cycle is high and the temperature gradient on the return oil side continuously decreases in the multi-point sampling sequence of inlet and return oil temperatures. The system observes the temperature recovery delay and gradient changes on the return oil side in fixed time windows. If the gradient decreases and the recovery delay increases within a continuous time window, and the ambient humidity is in a high range, this situation is marked as "frost trend." If, under the above trend, the fan speed curve and compressor duty cycle curve fail to recover the normal temperature gradient in subsequent time windows, this situation is upgraded to "frost occurrence." After completing the trend and occurrence judgment, the system generates a "defrosting label," which is given in a graded manner, with no frost, light frost, and heavy frost corresponding to different treatment recommendations. For light frost levels, the system recommends entering a temporary section for blower overflow defrosting in the next cycle of the thermal control command, and setting the compressor duty cycle to pulse operation; for heavy frost levels, the system recommends using short-time shutdown defrosting or long-interval pulse defrosting within the safety boundary, and provides "defrosting priority prompt" for S510 so that power and frequency concession configuration is prioritized when confirming the consistency of the liquid level return oil dual channel and the consistency of grade concession and guided reset.

[0115] Step S400 includes at least steps S410-S430:

[0116] S410. Obtain the standardized data and the viscosity estimation parameters, perform load soft measurement and anti-stagnation machine coordinated load estimation, and obtain the load estimation parameters;

[0117] The control system synchronously reads the standardized data and viscosity estimation parameters via the data bus. The standardized data is a dataset formed after sampling alignment, noise reduction, and dimension unification. Specifically, it includes oil pressure timing, multi-point sampling sequences of inlet and outlet oil temperatures, outlet oil status sequences, liquid level status sequences, main motor current and voltage timing, power factor timing, main contactor, star contactor, and delta contactor status sequences, main pump and standby pump pressure boosting stage markers and starting current trajectories, and ambient temperature and humidity sequences. The viscosity estimation parameters are output in step S330 and describe the rheological characteristics of the oil in different temperature ranges using temperature zones and priority markers. This step first establishes a time window corresponding to the current crushing cycle, and based on the most recent release and switching records, aligns the recent data of the main motor current and power factor with the oil pressure timing and outlet oil status sequences, ensuring that the load soft measurement unfolds at a time position consistent with the actual stress state of the equipment.

[0118] Specifically, the system focuses on observable indicators of "material layer thickness variation and ore inclusion degree," extracting load-related feature segments from the standardized data without adding expensive new sensors. First, the system identifies segments of pressure fluctuations corresponding to the rising phase of the main motor current in the hydraulic pressure time series, distinguishing between stable and abrupt segments, and confirms whether the pressure fluctuations are triggered by changes in oil circuit damping by combining the return oil state sequence. Second, the system compares the relative changes in the power factor time series and the main motor current time series to identify coupling segments between electromagnetic and mechanical loads, used to infer the ore inclusion degree within the crushing chamber. Third, the system reads the correspondence between the multi-point sampling sequence of inlet and return oil temperatures and the viscosity estimation parameters, mapping the rheological characteristics of different temperature zones to corrections for hydraulic pressure damping and bearing friction, thus eliminating estimation biases under the same operating conditions in cold and hot oil. The above features are uniformly organized into a load soft measurement input set within the time window. The system performs segment-by-segment evaluation on the input set to obtain qualitative and quantitative results for "instantaneous load level", "material layer change trend" and "intercalation risk level".

[0119] After completing the segmented evaluation, the system converts the evaluation results into structured "load estimation parameters". To facilitate subsequent linkage control, the load estimation parameters include at least the following items: First, load amplitude item, indicating the load range and rate of increase limit that the main drive side can withstand within the current cycle; Second, material layer trend item, indicating the duration and confidence level of material layer thickening or thinning; Third, ore inclusion risk item, indicating the ore inclusion risk level and its corresponding time position in the electrical parameter segment and hydraulic pressure segment; Fourth, allowable adjustment item, providing suggestions for the allowable feed increment and discharge port stroke step distance within the current time window, along with viscosity correction marks related to the temperature zone, to ensure that subsequent curve configuration can use different step distance upper limits under high or low viscosity oil conditions. The system writes the load estimation parameters into the data channel as the sole input for step S420; at the same time, it writes back the viscosity correction flag used in this step to the parameter reference table, so that step S420 can directly inherit the same temperature range context when configuring the curve; in addition, the system pushes the load amplitude entry and the ore inclusion risk entry to the input list of step S510 in the form of reference keys, for the pre-occupancy constraints of power and frequency concession during subsequent consistency confirmation.

[0120] S420. Configure the load soft measurement and anti-blocking machine coordination curve from the load estimation parameters, perform feed control and ore discharge control, and obtain the linkage control sequence.

[0121] The control system reads and analyzes the load estimation parameters, and constructs a "load soft measurement and anti-stagnation coordination curve" based on load amplitude entries, material layer trend entries, intercalation risk entries, and allowable adjustment entries. To ensure consistency across stages, the system simultaneously reads the duty cycle segment from the thermal control command output in step S320 as an environmental constraint, which is only used to determine the travel and cycle boundaries of the curve in high cold load or high hot load sections, without changing the decision-making principle of this step, which is based on the load estimation parameters. The system first selects a set of benchmark curves matching the current machine model from the curve library, including the feed-side increase / decrease curves and cycle time curves, and the discharge-side opening / closing step distance curves and cycle time curves, and uses the load amplitude entries as the initial scaling factor for the curve intensity. Further, the system analyzes the material layer trend entries. For a thickening trend, the upper limit of the slope of the feed-side increase curve is limited, while the upper limit of the discharge-side opening step distance and cycle time frequency are increased simultaneously to prevent the material layer from continuing to accumulate. For a thinning trend, the upper limit of the feed-side increase curve is released and the upper limit of the discharge-side step distance is reduced.

[0122] After completing the baseline scaling and trend limiting, the system introduces an inter-ore risk item to rewrite the curve in a structured manner. Specifically, when the inter-ore risk item is marked as high-level, the system inserts a "peak suppression segment" into the feed-side curve. This peak suppression segment is linked to the rate of increase limit in the load amplitude item, forcing a smaller increase in feed rate within several cycle periods. Simultaneously, a "load release segment" is inserted into the discharge-side curve, increasing the opening step and cycle frequency to release the stress concentration in the crushing chamber in a time-sharing manner. When the inter-ore risk item is marked as low-level, the system retains the smooth transition shape of the curve, setting a buffer zone only near the upper limit indicated by the allowable adjustment item to ensure that short-term load fluctuations do not immediately trigger a shock adjustment. After the above curve adjustments are completed, the system discretizes the curve on the time axis into control items that can be issued, forming a "linked control sequence". The linkage control sequence includes at least the time sequence of the feed inverter frequency setting, the time sequence of the discharge actuator stroke setting, and the phase linkage rules between the two; it also includes the cycle alignment rules and stroke upper limit limit related to anti-stagnation, so as to ensure that the feed and discharge sides have a consistent force release path within the same time window.

[0123] During sequence generation, the system continuously references the viscosity correction flag in the adjustable entries. If the flag indicates that the current temperature range is high, a "slow window" is added to the linkage control sequence to limit the rate of change of the feed inverter frequency setting and proportionally converge the upper limit of the step distance setting for the discharge port stroke. If the temperature range is low, the rate of change and the upper limit of the step distance are appropriately relaxed while ensuring the boundary of the load amplitude entry. The system writes the linkage control sequence into the data channel as the direct input for step S430; and writes back the curve selection record and limiting parameters used in this step to the fingerprint sedimentation record of step S610 so that step S620 can update the curve library and the upper limit of the step distance when generating the parameter update set. At the same time, the system pushes the phase linkage rules of the linkage control sequence to the input list of step S520 with a reference key so that the graded yielding strategy can perform consistent trimming on both sides of the feed and discharge when yielding is required.

[0124] S430. Perform load soft measurement and anti-stagnation machine coordinated impact assessment on the linkage control sequence to generate impact index parameters;

[0125] The control system reads the linkage control sequence from the data channel and synchronously reads the standardized data as a reference throughout the execution of the sequence to complete the joint evaluation of the impact on the mechanical, electrical, and hydraulic sides. This step first maps the inflection points of the feed inverter frequency setting and the discharge outlet actuator stroke setting onto the same time axis according to the phase linkage rules of the linkage control sequence, establishing an "action event table." The system then extracts the oil pressure sampling segment, main motor current sampling segment, and power factor sampling segment adjacent to each action event from the standardized data, and reads the return oil state sequence and liquid level state sequence to identify whether the action event triggered transients in the oil circuit damping and liquid level fluctuations. For events involving an increase in the feed rate, the system focuses on observing the upward surge of the main motor current sampling segment and the decrease in the power factor, and searches for any sudden changes in the oil pressure sampling segment within the same time window. For events involving an increase in the discharge rate, the system focuses on observing the downward surge of the oil pressure sampling segment and the short-term stability of the return oil state, and searches for any signs of a brief drop followed by a subsequent rise in the main motor current within the same time window, in order to identify potential ore inclusion release and secondary compression.

[0126] The system summarizes the observations obtained around each action event into "event impact entries". Each event impact entry contains at least electrical-side impact markers, mechanical-side impact markers, and oil circuit-side impact markers, along with the corresponding curve source and limiting parameter source, used to quickly locate the curve segment or limiting strategy that caused the impact when tracing is required. Furthermore, the system performs a continuous inspection along the time axis of the action event table, looking for situations where several consecutive events occur in a short period of time. If such a cluster exists, the system aggregates them into "impact clusters" and reads the temperature zone marker of the viscosity estimation parameters within the corresponding time window to determine whether the impact cluster is related to high or low viscosity conditions. For impact clusters that overlap with high viscosity temperature zones, the system records "rheological correlation symbols" in the entry, prompting subsequent maintenance strategies to fine-tune the oil temperature window and duty cycle upper limit in conjunction with the impact cluster; for impact clusters that overlap with low viscosity temperature zones, the system records "cycle time correlation symbols", prompting subsequent parameter optimization to prioritize the rearrangement of cycle time and phase.

[0127] After completing the two-level aggregation at the event level and cluster level, the system generates "impact index parameters". These impact index parameters are output as a structured set, including at least electrical impact levels, mechanical impact levels, and hydraulic impact levels, with each level accompanied by a primary source entry and a suggested trimming direction. To maintain a closed loop across modules, the system writes the impact index parameters into the data channel as direct input to step S520, used to determine the priority of power limiting control or frequency limiting control in the graded yielding strategy. Simultaneously, the system writes the impact cluster and its associated rheological or clockwise related symbols into the fingerprint sedimentation record of step S610, providing a reference key for generating the parameter update set in step S620. This allows the curve library, step size limit, clockwise phase, and oil temperature window to be adaptively fine-tuned based on fingerprint characteristics in subsequent cycles. Furthermore, the system synchronizes the key timestamps of the event impact entries and the action event table to step S510, ensuring that the consistency of the dual-channel oil return and guided reset is determined by referring to the same event boundary, avoiding repeated yielding or missed yielding for the same event.

[0128] Step 500 includes at least steps S510-S530:

[0129] S510. Obtain the standardized data, the thermal control command, the load estimation parameters, and the switching consistency identifier; perform consistency confirmation of the dual-channel liquid level return oil and the staged yielding and guided reset; and obtain the consistency result.

[0130] In step S510, the control system synchronously reads the standardized data, the thermal control command, the load estimation parameters, and the switching consistency identifier via the fieldbus and the edge controller. The standardized data is a unified data set after sampling alignment and denoising, including oil pressure timing, multi-point sampling sequences of inlet and outlet oil temperatures, return oil status sequences, liquid level status sequences, main motor current and voltage timing, power factor timing, and main contactor, star contactor, and delta contactor status sequences, etc. The thermal control command is a periodic scheduling sequence output by S320, including heater power percentage curves, compressor duty cycle curves, fan speed curves, and constraints such as minimum start / stop intervals and mutual exclusion windows. The load estimation parameters are a set of structured entries obtained by S410 based on the viscosity estimation parameters and the standardized data, including load amplitude entries, material layer trend entries, ore inclusion risk entries, and allowable adjustment entries. The switching consistency identifier is a timing consistency symbol for star-to-delta switching output by S230, used to counteract contactor adhesion and interlocking failure. To ensure consistency in the judgment, this step first establishes the current judgment time window based on the period boundary of the thermal control command, and maps the switching instant corresponding to the switching consistency identifier into the same time window. Furthermore, the oil pressure, return oil, liquid level and electrical parameters in the standardized data are synchronized and aligned to form a comparison basis that connects multiple circuits.

[0131] Specifically, the system first performs a dual-channel consistency confirmation of the liquid level and return oil. Within the judgment time window, the controller performs a dual-channel linkage search on the liquid level state sequence and the return oil state sequence: when the return oil state sequence reports smooth return oil flow, the liquid level state sequence should show a stable or slowly decreasing trend; when the return oil state sequence reports poor return oil flow, the liquid level state sequence is allowed to rise to a limited extent within a short time window. The system uses the oil pressure timing in the standardized data as evidence to check whether the above channel correlation matches the oil pressure drop; if a mutually exclusive situation occurs, such as "smooth return oil flow but abnormal liquid level rise" or "poor return oil flow but no obvious oil pressure disturbance", it is marked as dual-channel inconsistency in this cycle. Furthermore, the system combines the fan and compressor duty cycle curves of the thermal control command to identify whether the heat exchange stage on the cold source side causes a short-term coupling effect on the liquid level and return oil; if there is a short-term liquid level fluctuation caused by changes on the cold source side, and the fluctuation is within the mutually exclusive window, it is removed according to the operating constraints and is not considered an inconsistency mark. After completing the channel layer determination, the system enters a pre-check for consistency confirmation of graded retreat and guided reset. First, based on the load amplitude and ore inclusion risk items in the load estimation parameters, the system assesses whether there are concentrated stress sections requiring retreat triggering within the current time window. Second, the system checks the step response of the main motor current and power factor against the switching consistency flag at the critical moment of star-shaped hold-up and delta-shaped switch. If the check passes, the guided reset path can reference the constraint of "maintaining the current switching cycle." If the check fails, the guided reset path needs to insert the pre-action of "preheating before switching and oil circuit unobstructed verification." The above three determination results are structured and aggregated into a "consistency result" within the controller, including dual-channel consistency flags, retreat trigger suggestions, and guided reset preconditions, and includes a reference key aligned with the time window. The system writes the consistency result into the data channel as one of the only inputs to step S520. At the same time, it fills the key conclusions of the consistency result back into the exception buffer, so that step S530 can directly call it when generating the reset step sequence, thus realizing a continuous link from judgment to strategy to reset.

[0132] S520. Configure a dual-channel consistency and graded yielding and guided reset yielding strategy for liquid level return oil from the consistency results and the impact index parameters, perform power limiting control and frequency limiting control, and obtain an abnormal grade code.

[0133] The control system reads and parses the consistency results and the impact index parameters. The impact index parameters, output by S430, are a summary of event-level and cluster-level assessments of impacts on the electrical, mechanical, and hydraulic sides, containing suggestions for labeling and pruning directions for concentrated impact sources. This step establishes a strategy configuration context within the controller: First, the dual-channel consistency flag of the consistency results is used as the strategy entry point to determine whether the current cycle requires priority integration of oil circuit and liquid level channels; second, the yield trigger suggestion and guided reset precondition in the consistency results are used as pruning boundaries to limit the scope and duration of the strategy; third, the impact index parameters are used as adjustment weights to perform hierarchical mapping of the strategy's intensity and rhythm, so that areas with higher impact receive higher priority suppression and diversion. In this context, the system sequentially constructs the "liquid level return oil dual-channel consistency and graded yield and guided reset yield strategy," and injects power limiting control and frequency limiting control into the strategy core.

[0134] Specifically, the system first performs consistency integration at the channel layer: when the consistency result indicates inconsistency between the two channels, the strategy immediately locks the rate of change boundaries on both the feeding and discharging sides and cross-compares them with the mutually exclusive windows of the thermal control command to ensure that changes on the cold source side do not cause superimposed disturbances with channel integration. Further, the system enters a graded yielding configuration: based on the level label and source entries of the impact index parameter, the target upper limit and descent cycle of the power limiting control are determined, and the minimum value between this upper limit and the load amplitude entry in the load estimation parameter is selected to ensure that the power limiting control does not exceed the current drive capability boundary. In the frequency limiting control on the feeding side, the system introduces segmented cycles for the set frequency of the feeding inverter, prioritizing stricter frequency clipping within the time window corresponding to the impact source, and mitigating the impact outside this time window according to the yielding trigger suggestion shown by the consistency result. For cases with high risk of ore inclusion and impact cluster aggregation, the system simultaneously inserts a fine-tuning of the opening on the discharging side that is compatible with channel integration to avoid intracavity force bias caused by unilateral yielding. Through the combination of channel integration, power limiting control, and frequency limiting control, the system forms a set of strategies for the current cycle and maps the set to an "abnormal classification code". The abnormal classification code encodes the strategy strength, triggering conditions, and holding limits with a single identifier, facilitating rapid transmission between the execution layer and the human-machine interface. The metadata pointed to by this identifier includes the power limiting control target, frequency limiting control cycle, channel integration holding duration, and a reference key for allowed pre-reset conditions. The system writes the abnormal classification code into the data channel as direct input to step S530, and simultaneously binds the abnormal classification code to the reference key of the consistency result, ensuring that the reset process can restore the original cycle's judgment context during subsequent generation. Furthermore, the system synchronously registers the abnormal classification code in the fingerprint accumulation record of S610, so that S620 can fine-tune the gating parameters, switching parameters, and yielding parameters based on the long-term hierarchical distribution when generating the parameter update set.

[0135] S530. Configure the liquid level return dual-channel consistency and graded concession and guided reset process for the abnormal classification code, and generate a reset step sequence.

[0136] In step S530, the control system reads the anomaly classification code and, based on the strategy metadata bound to the identifier and the consistency result, performs a reset process configuration to generate an executable "reset step sequence". To ensure that the process matches the actual state of the equipment, the system first restores the time window and reference key of the current cycle in the controller, loads the dual-channel consistency flag, yield trigger suggestion, and guided reset preconditions from the consistency result, and performs a secondary check with the mutual exclusion window of the thermal control command to confirm that the reset action will not conflict with the duty cycle change on the cold source side. Further, the system maps the anomaly classification code to a reset path type: when the identifier corresponds to channel integration priority, the reset path follows the main line of "channel verification - partial yield release - reset confirmation"; when the identifier corresponds to impulse suppression priority, the reset path follows the main line of "power boundary reload - frequency beat recalibration - reset confirmation"; when the identifier contains both types of priorities, the reset path follows the main line of "channel pre-setting - power and frequency synchronization reload - reset confirmation", and the step distances at both ends are uniformly controlled to the same holding duration.

[0137] Based on the aforementioned path types, the system configures each reset node specifically. At the "Channel Verification" node, the system instructs the field terminal to sequentially perform level sensor verification, return oil switch signal rereading, and oil pressure segment inspection according to the preconditions of the consistency results. Within the judgment window, the system maintains the feeding and discharge in a static or low-amplitude state until the dual-channel consistency flag is restored to consistency. At the "Partial Retreat Release" node, based on the power limit control target and frequency limit control rhythm attached to the anomaly classification code, the system instructs the main drive side to maintain the upper power limit, instructs the feeding side to gradually rise or fall in segmented rhythms, and performs micro-step opening and closing of the discharge side's stroke to eliminate residual force within the cavity. At this node, the system simultaneously checks the allowable adjustment entries in the load estimation parameters to avoid exceeding the allowable step distance and rate of change. At the "Power Boundary Reload" node, the system reloads the power limiting control target to the execution layer in the form of a hold duration and a backoff threshold, ensuring that the power change in the first cycle after reset still falls within the graded constraints. At the "Frequency Cycle Recalibration" node, the system resets the segmented cycle parameters on the feeding side based on the anomaly grade code and the yield trigger suggestion in the consistency result, ensuring that the cycle peak avoids the time window that may form impact clusters. Further, at the "Reset Confirmation" node, the system sequentially checks whether the state sequence of the main contactor, star contactor, and delta contactor is consistent with the switching consistency identifier, checks whether the oil pressure, return oil, and liquid level meet the stability boundaries in the consistency result, and records the confirmation timestamp and pass mark.

[0138] After the above nodes are configured, the control system connects them in series to form a "reset step sequence". The reset step sequence is a structured set of execution entries, each specifying the action object, set value or duration, entry and exit conditions, failure fallback path, and re-verification entry. Each execution entry is associated with the anomaly classification code and the reference key of the consistency result, allowing for branch selection based on field feedback during execution. The system writes the reset step sequence into the data channel as a direct input to S610, used for fingerprinting in remote diagnostics and parameter adaptive write-back. Simultaneously, the anomaly classification code and key entries of the reset step sequence are copied to the operation recorder, allowing S620 to perform consistent write-back of gating parameters, switching parameters, and yield parameters when generating the parameter update set. At this point, the consistency result of step S510 is fully used in step S520 and encoded into the anomaly classification code. The anomaly classification code of step S520 is fully used in step S530 to generate the reset step sequence, forming a closed loop of "determination-strategy-reset". At the same time, the reset step sequence and the anomaly classification code are deposited and written back in the S600 link to achieve cross-cycle traceability and reusability.

[0139] Step S600 includes at least steps S610-S630:

[0140] S610. Obtain the reset step sequence, the abnormality classification code, and the switching gap parameter; perform remote diagnosis and parameter adaptive write-back fingerprint deposition to obtain fingerprint data.

[0141] In S610, the edge control unit synchronously reads the reset step sequence from the execution record channel according to the same time base as S530; simultaneously, it reads the anomaly classification code generated by S520 and bound by S530 from the strategy encoding channel; and then, it reads the switching gap parameter output by S230 from the device self-test channel. To ensure data comparability within the same time window, the system first performs timestamp alignment and cycle boundary alignment on the three types of inputs, mapping the reset step entries, classification identifier entries, and gap parameter entries to the current diagnostic window; furthermore, it associates the reset entries with their corresponding classification identifiers one-to-one using reference keys to prevent entries from drifting outside the cycle.

[0142] Specifically, the system calls the operational feedback collected on-site to read back the execution status of each execution item in the reset step sequence, including the action object, set value or holding duration, entry and exit conditions, failure rollback path, and re-verification entry. For items that cannot be directly verified by the on-site feedback, the system uses standardized data such as oil pressure sequence, oil return status sequence, liquid level status sequence, and main motor current and power factor timing sequence for corroboration matching to confirm whether they were actually triggered within the judgment window. To eliminate the impact of short-term fluctuations caused by disturbances on the cold source side, the system simultaneously loads the thermal control command fragment generated by S320, compares it with the mutual exclusion window of heating and compressor duty cycles, marks the time periods that may cause short-term fluctuations in liquid level or oil return, and processes them with immune marking during subsequent archiving to ensure that such fluctuations are not included in the violation set.

[0143] After alignment and verification are completed, the system performs remote diagnostic modeling. First, the system uses the anomaly classification code as an index to collect strategy metadata such as power limiting control targets, frequency limiting control cycles, channel integration holding duration, and preconditions for guided reset into the diagnostic context. Second, the system re-verifies the key moments of star-shaped holding and angle-shaped switching based on the historical segments of the switching gap parameters and the switching consistency identifier (which has been generated in S230 and entered into the operation record channel), forming switching consistency verification entries. Third, the system aggregates the hydraulic pressure segment, liquid level segment, return oil segment, and electrical parameter segment to generate a set of operating condition segments corresponding to the reset node, which describes the continuous state before, during, and after reset.

[0144] Based on this, the system enters the fingerprint accumulation stage of parameter adaptive write-back. The system generates a fingerprint master record for each cycle, attaching the following information in the form of entries: time window marker, the anomaly classification code, the switching gap parameter, the execution receipt of each step of the reset sequence, the switching consistency verification entry, the channel integration hold duration, the actual achievement degree of the power limiting target and frequency limiting cycle, and the reset confirmation mark. To facilitate cross-cycle comparison, the system performs similarity matching between the fingerprint master record and historical records. If similar fault clusters are found to occur repeatedly, repetition count and interval statistics entries are added to the master record; if similar scenarios show differences between different individual devices, individual difference annotation entries are added to the master record. After accumulation, the system outputs the structured results as "fingerprint data" and transmits it to S620 through the data channel; simultaneously, the summary key of the fingerprint master record is written to the maintenance log for quick retrieval by summary later.

[0145] S620. Configure remote diagnostic and parameter adaptive write-back maintenance strategies from the fingerprint data, generate rotation strategies and window limit strategies, and obtain parameter update sets;

[0146] In S620, the system uses the fingerprint data as the sole input source to start the policy generation engine. During the engine initialization phase, the system reads the fingerprint master record set from the previous statistical interval, parses the gate-related release condition entries, the handover-related gap or beat entries, and the yield-related power limiting or frequency limiting entries, and categorizes them into three dimensions: gate control dimension, handover dimension, and yield dimension. Further, the system performs trend summarization within each dimension: in the gate control dimension, it aggregates the oil pressure arrival time, the number of times the oil temperature window is established, the failure patterns, and the deviations from the release conditions; in the handover dimension, it aggregates the star-shaped hold duration, the angle-shaped handover trigger point, and the stability of the handover consistency token; in the yield dimension, it aggregates the actual achievement of the power limiting target and the actual execution of the frequency limiting beat.

[0147] After aggregation, the system enters the maintenance strategy configuration stage. First, based on the gating dimension aggregation results, the system generates candidate window limit strategies for remote diagnosis and parameter adaptive write-back. These candidates include suggestions for fine-tuning the upper and lower boundaries of the oil temperature window and suggestions for the time window width for confirming oil pressure arrival. Second, based on the switching dimension aggregation results, the system generates suggestions for fine-tuning the switching gap and recalibration entries for switching consistency verification, used to constrain the opening and closing intervals of the contactor group at critical moments. Third, based on the yield dimension aggregation results, the system generates suggestions for fine-tuning the power limiting target and frequency limiting cycle time, as well as suggestions for holding duration. The candidates in these three directions will undergo conflict resolution within the same strategy canvas: when the window limit strategy may overlap with the switching gap suggestion in time, the system prioritizes retaining the switching gap suggestion and shifts the effective range of the window limit strategy forward or backward outside the mutually exclusive window; when the yield dimension suggestion and the gating dimension suggestion overlap in the same cycle and may affect the release order, the system prioritizes retaining the gating dimension suggestion and sets the yield dimension suggestion to be executed with a delay during the "first load ramp-up phase after release".

[0148] After the remote diagnostic and maintenance strategy is determined, the system proceeds to configure the rotation strategy at the device level. The system reads indirect characterization entries of the health of the main and standby pumps from the fingerprint data (e.g., pressure boost duration distribution, starting current characteristics, and stability of the pressure build-up curve), and combines these with repetition count and interval statistics to provide rotation cycle suggestions and abnormal bypass suggestions for the main and standby pumps. This suggestion is then checked for consistency with the aforementioned window limit strategy to ensure that the rotation does not conflict with switching gaps or gating release conditions. Finally, the system packages the window limit strategy, switching gap suggestions, fallback maintenance suggestions, and rotation strategy into a unified "parameter update set." This parameter update set is presented as a set of entries, clearly distinguishing between gating parameter entries, switching parameter entries, and fallback parameter entries. Each entry is marked with its effective conditions, hold duration, fallback threshold, and monitoring signal source. Simultaneously, a common reference key is generated for the three types of entries, enabling them to be committed at the same transaction boundary during S630 write-back. The system outputs the parameter update set to the data channel as the sole input to the S630; at the same time, it writes the fingerprint digest key used for this policy generation into the maintenance log to facilitate subsequent tracking of the policy source.

[0149] S630. Use the parameter update set for remote diagnosis and parameter adaptive write-back process to update the gating parameters, switching parameters and yielding parameters.

[0150] In S630, the system uses the parameter update set as input to initiate a phased write-back process. First, the system performs a pre-verification check to verify whether the reference key of the parameter update set is consistent with the current operating cycle of the device. After the verification passes, the system enters the gray-scale write-back stage. Gray-scale write-back prioritizes gated parameter entries: when the device is in standby or low-load steady state, the system writes the upper and lower boundary fine-tuning values ​​of oil temperature and the width of the oil pressure confirmation time window into the gated parameter set, and continuously monitors the natural fluctuations of the oil pressure and oil temperature sequences with a short-term observation window. If the rollback threshold is not reached within the observation window, the gated parameter entry is marked as effective; if the rollback threshold is reached, the system automatically calls the rollback entry in the parameter update set, rolls the gated parameters back to the previous cycle state, and adds a rollback record to the fingerprint channel.

[0151] The system enters the switching parameter write-back phase. Between the neutral window during the star-shaped holding phase and the interlock window before the delta-shaped switch, the system writes the fine-tuning value of the switching gap and the consistency verification re-calibration entries twice to ensure that the contactor group's action intervals at critical moments are subject to new constraints. After writing, the system triggers a controlled switching exercise. During the exercise, the contactor state sequence and the timing sequence of the main motor current and power factor are recorded at a high sampling rate, and immediately compared with the switching consistency flag given in S230. If the comparison is consistent, the switching parameter entries are marked as effective; if the comparison is inconsistent, the system performs a partial rollback, only rolling back the switching parameter entries while keeping the gating parameter entries unchanged to avoid affecting the already stable gating boundaries.

[0152] Example 2: Figure 2 A structural block diagram of a cone crusher control system according to an embodiment of the present invention is shown. Figure 2 As shown, the structure may include:

[0153] The health rating module 01 is used to acquire multi-source observation and health characterization data, perform sampling alignment, noise reduction, element extraction and health rating calculation processing to obtain a health rating; the data includes oil pressure, oil temperature, oil return status, liquid level status, main motor current and voltage, power factor, contactor status, main pump and standby pump pressure boosting stage markings and ambient temperature and humidity data. Specifically, the system receives multi-source observation data from the sensing layer, including oil pressure sensor, oil temperature sensor, return oil switch, level relay, main motor current and voltage sampling module, power factor acquisition module, contactor status feedback loop, main pump and standby pump monitoring loop, and ambient temperature and humidity detection unit. Under unified master clock and dimensional constraints, sampling alignment and band-limited filtering are performed to form standardized data. Time window segmentation and element extraction are performed on the standardized data to generate an element sequence consisting of oil pressure elements, oil temperature elements, electrical parameter elements, contactor switching elements, return oil and level dual-channel elements, pump pressure boosting elements, and ambient temperature and humidity elements. Based on the element sequence, pump health calculation channels, switching health calculation channels, and lubrication operation health calculation channels are established. A health score is generated through the collaborative processing of a slow-change tracker and a steady-state window. The health score is transmitted to the switching control module as a gating start-up judgment input, and the element sequence and health score are associated and stored in the health characterization data channel for the oil temperature and viscosity control module to call.

[0154] The switching control module 02 is used to perform gated start-up and star-delta consistency release judgment, switching sequence configuration and execution, and consistency verification and evaluation of the switching process, obtaining switching consistency identifiers and switching gap parameters. Specifically, it receives health scores and standardized data from the health scoring module, identifies segments of the oil pressure sequence and return oil state sequence under the lubrication-first principle, and generates a release command containing the remaining pre-lubrication time and switching adjustment suggestions by combining the pump health score and switching health score; it completes the fine-tuning configuration of the initial values ​​of star-delta holding and delta switching based on the release command, generates a draft switching sequence through contactor linkage initialization test, and sends it to the control task queue; during execution, it collects the transient curves of main motor current and oil pressure in real time, dynamically adjusts the switching buffer amount according to the boundary monitoring results, and forms a switching control sequence containing drive commands and sampled data; it performs star-delta holding integrity verification and switching gap cycle identification on the switching control sequence, generates a switching consistency identifier and switching gap parameters, outputs them to the oil temperature and viscosity control module, and writes the self-test record into the data channel for remote diagnosis and maintenance module to call.

[0155] The oil temperature and viscosity control module 03 is used to acquire switching gap parameters, perform oil temperature predictive control and short-term prediction of cold and heat coordination, heating and compressor scheduling, and viscosity correction and defrosting judgment processing, generating viscosity estimation parameters and defrosting indicators. Specifically, it receives switching gap parameters from the switching control module and aligns them with the inlet and outlet oil temperature sequences in the standardized data. After establishing transient disturbance indicators, it performs rolling short-term prediction to generate prediction results containing temperature trend entries and heat demand entries. Based on the prediction results, it configures the heater power percentage curve, compressor duty cycle curve, and fan speed curve, and generates thermal control commands by combining mutual exclusion window constraints. During execution, it tracks the oil temperature response speed and return oil state changes, generates viscosity estimation parameters through rheological feature cross-validation, and determines the frosting level and generates a defrosting indicator based on the correspondence between the ambient temperature and humidity sequence and the compressor duty cycle curve. It transmits the viscosity estimation parameters and defrosting indicator to the load estimation and control module, and writes the execution record of the thermal control command to the exception buffer for the exception handling module to call.

[0156] The load estimation and control module 04 is used to perform load soft measurement and anti-blocking machine coordinated load estimation based on viscosity estimation parameters. It identifies the frequency band by calculating the cross-spectral density and coherence coefficient of oil pressure and current. The feeding and discharge control adopts the model predictive control paradigm and configures the time series of the feed inverter frequency setting and the discharge port actuator stroke setting. The impact assessment processing calculates the normalized cross-correlation peak value of the control sequence and the rate of change of the load estimation parameters to generate the impact index parameter. Specifically, viscosity estimation parameters are received from the oil temperature and viscosity control module and cross-spectral analysis is performed with the main motor current timing data in the standardized data to determine the load-related frequency band. Short-time spectral energy is then aggregated and load estimation parameters are generated through convex optimization fusion. A model predictive control relationship is constructed using the load estimation parameters as the controlled state. Under the condition of satisfying the actuator rate limit, a linkage control sequence for the feed inverter frequency setting and the discharge port stroke setting is generated. The electrical and mechanical impacts caused by action events are monitored in real time, and impact index parameters are generated by calculating the normalized cross-correlation peak value. The impact index parameters are output to the anomaly handling module, and the phase linkage rules of the linkage control sequence are written into the graded yield strategy buffer.

[0157] The anomaly handling module 05 is used for confirming the consistency of the dual-channel oil return at the liquid level, the consistency of graded retreat and guided reset, power limiting and frequency limiting control, and the configuration of the reset process, generating a reset step sequence and anomaly classification code. Specifically, it receives the impact index parameter from the load estimation and control module and cross-compares it with the liquid level state sequence in the standardized data. It generates a dual-channel consistency marker through oil pressure corroboration and cold source-side coupling analysis. Based on the impact index parameter level, it configures the power limiting control target and frequency limiting control cycle, and generates anomaly classification code by combining the ore inclusion risk item in the load estimation parameters. According to the reset path type mapped by the anomaly classification code, it sequentially configures the channel verification node, the local retreat release node, and the power boundary reload node to form a reset step sequence containing the action object and the failure retreat path. The reset step sequence and anomaly classification code are output to the remote diagnosis and maintenance module, and the reset confirmation timestamp is written to the operation recorder for the switching control module to call.

[0158] The remote diagnostics and maintenance module 06 is used for remote diagnostics, parameter adaptive write-back fingerprint accumulation, maintenance strategy generation, and write-back process processing based on the reset step sequence, anomaly classification code, and switching gap parameters, updating gating parameters, switching parameters, and yield parameters. Specifically, it receives the reset step sequence and anomaly classification code from the anomaly handling module, performs timestamp alignment with the switching gap parameters provided by the switching control module, and generates a fingerprint master record by matching execution receipts and standardized data corroboration. It performs trend summarization of the gating dimension, switching dimension, and yield dimension on the fingerprint master record set to form a parameter update set consisting of oil temperature window fine-tuning suggestions and switching gap recalibration entries. When the equipment is in a low-load steady state, it writes back the gating parameter entries and switching parameter entries in stages. After confirming the effective status through switching drills and trajectory tracking, it writes back the yield parameter entries. It transmits the transaction completion token to the switching control module and the anomaly handling module for the next cycle strategy assembly, and appends the write-back results to the fingerprint channel to form a cross-cycle closed loop.

[0159] Figure 3 This document provides an overall electrical schematic diagram of a cone crusher control system as an embodiment of the present application. As the power supply and execution architecture assembly of the control system, it integrates power distribution, short-circuit protection, and actuator drive functions, providing a global hardware implementation foundation for the control methods of the aforementioned embodiments.

[0160] See Figure 3 The system's electrical architecture is powered by a three-phase power supply (L1, L2, L3, N), introduced through a main circuit breaker (-QF1, such as 630A), providing overcurrent and short-circuit protection for each branch. Its core components and functions are as follows:

[0161] Power Distribution and Protection Unit: The main power supply, after passing through -QF1, is distributed to multiple branch circuit breakers (-QF2 to -QF7). Each branch circuit breaker independently protects a functional unit, including:

[0162] Main shaft drive unit: powered by the -QF2 branch, and controlled by contactor -KM1 to start and stop the main motor M1. This is the core power source for performing crushing operations.

[0163] The lubrication unit comprises two independent oil pump branches (-QF3 and -QF4), which control oil pump motors M2 (No. 1) and M3 (No. 2) via contactors -KM2 and -KM3, respectively. This structure physically realizes the "dual-pump redundant lubrication unit with one pump in use and one in standby" as described in the claims. The controller can perform the "main pump and standby pump pressure boosting switching" operation by controlling the energization and de-energization of -KM2 and -KM3.

[0164] Temperature control unit: Includes heating branch (-QF5), refrigeration compressor branch (-QF6), and cooling fan branch (-QF7), which control the corresponding actuators via contactors -KM4, -KM5, and -KM6 respectively. This is the hardware foundation for realizing the "coordinated cooling and heating scheduling" method. The controller precisely manages the oil temperature by coordinating the on / off states of these three branches.

[0165] Control logic implementation: Figure 3 The connection relationship from the high-voltage power circuit to the low-voltage control circuit is clearly illustrated. The coils of each contactor (-KM1 to -KM7) are controlled by the digital output module (DO) of the PLC. All commands issued by the controller, such as "start the main unit," "switch the oil pump," "start heating," or "start cooling," ultimately energize the corresponding contactor coil, thereby connecting the main circuit and driving the motor or heater to operate. Simultaneously, the auxiliary contacts of each circuit breaker and the status signals of the contactors can be fed back to the controller's input module, forming a closed-loop control and status monitoring system.

[0166] This overall circuit diagram embodiment demonstrates that the intelligent control system based on data-driven and health scoring described in this invention is built upon, for example... Figure 3 It is built upon a mature, reliable, and modular industrial electrical architecture. It defines the complete power and signal flow path from the total power input to each final actuator, fully demonstrating the feasibility and industrial applicability of the technical solution of this invention. That is, on a standard hardware configuration, through innovative software algorithms, it achieves intelligence, high reliability, and energy-saving effects that surpass traditional control.

[0167] Figure 4This application provides a schematic diagram of the core control circuit of a cone crusher control system. It details the electrical connection logic of the main motor drive unit, lubrication system control unit, and signal indication unit. In particular, it shows the complete control circuit of the main motor using a star-delta (Y-Δ) reduced-voltage starting method, providing a low-level drive and status feedback mechanism for the execution of the control method.

[0168] See Figure 4 The control circuit is powered by control transformer T1, which converts the 380V / 220V voltage to the safe voltage required by the control circuit. Its core components include:

[0169] Main motor star-delta reduced voltage starting unit: This unit is Figure 4 The core of the device consists of a main contactor (KM1), a star-shaped auxiliary contactor (KM2), a delta-shaped contactor (KM3), a thermal relay (FR1), and a time relay (KT1), which specifically realizes the soft-start control of the "conical main motor" described in claim 10.

[0170] Start-up process: When the controller (PLC) issues a start command (driving the intermediate relay KA1 to engage), the current flows through the following path: KA1 normally open contact closes → KT1 coil is energized → KM3 coil is energized (through KT1 instantaneous contact) → KM1 coil is energized (through KM3 normally open auxiliary contact) → KM2 coil is energized (through KM1 normally open auxiliary contact and KM3 normally closed auxiliary contact). At this time, the main motor starts in a star (Y) connection, the winding voltage decreases, and the starting current decreases.

[0171] Switching process: After the time relay KT1 completes its delay, its delayed-open contact cuts off the KM2 coil circuit, and its delayed-close contact connects the KM3 coil self-locking circuit. After KM2 is de-energized and released, KM3 remains engaged thanks to its self-locking circuit, and the main motor windings switch to a delta (Δ) connection, entering full-voltage normal operation. This process perfectly achieves the control objective of "suppressing the start-up impact of the main unit," and is the concrete hardware implementation of the "soft start" strategy recommended by the health rating model.

[0172] The lubrication system control and status feedback unit integrates the oil pump motor control circuit (e.g., via contactor KM4) and pressure switch signals (e.g., "pressure reached" indication). The start / stop commands for the lubrication pump are issued by the controller (e.g., driving KA2), and its operating status and fault signals (e.g., thermal relay FR2 activation) are fed back to the controller's input module via intermediate relay contacts. This forms a direct hardware interface for "acquiring lubrication system oil pressure and flow data" and realizing "dual-pump redundancy switching."

[0173] Signal Indication and System Integration: The various indicator lights in the diagram (such as "Main Unit Running," "Pressure Reached," and "Power Indicator") provide operators with an intuitive display of equipment status. More importantly, the coils of all intermediate relays (KA0-KA8) are driven by the controller's output points, and their contact states (such as the "Automatic / Manual" switch of KA4) are fed back to the controller as input signals. This clearly demonstrates how the core controller (PLC or industrial computer) described in this invention is seamlessly integrated with this mature industrial control circuit, thereby acquiring data and executing output decisions based on advanced intelligent algorithms.

[0174] This control loop embodiment demonstrates that the data-driven intelligent control system described in this invention does not replace traditional reliable control circuits, but rather enhances them with higher-level intelligent capabilities. Figure 4 The circuit shown is responsible for reliably performing basic operations such as "start-stop" and "switching", while the controller of this invention is responsible for making advanced decisions such as "health assessment", "predictive maintenance" and "optimized scheduling". Together, they constitute a complete, advanced and practical control system.

[0175] Figure 5 This diagram illustrates the manual and automatic control interface of a cone crusher control system, as provided in this embodiment. It details the switching logic, safety interlocks, and signal indication circuits of the lubrication system (oil pump, heater) in local manual mode and remote automatic mode. This interface is crucial for flexible and safe interaction between the intelligent control system and the underlying equipment.

[0176] See Figure 5 The control circuit is powered by a ~220V control power supply, and its core functions and connections are as follows:

[0177] 1. Manual / Automatic Mode Switching Unit: This function is implemented through a selector switch (not marked in the diagram but logically present) and intermediate relays (such as KA1, KA2, ...). As shown in the figure, commands such as "Start Main Oil Pump", "Stop Main Oil Pump", "Start Heating", and "Stop Heating" all have two parallel trigger paths:

[0178] Local manual mode: can be triggered directly by the operator pressing a button on site (such as "S9: Start main oil pump", "S10: Stop main oil pump").

[0179] Remote automatic mode: The core controller (such as PLC) described in this invention drives the corresponding output point to energize the intermediate relays (such as "-EMG13: start main oil pump" and "-EMG14: stop main oil pump"), and their contacts simulate button actions to achieve automatic control.

[0180] This design ensures a high degree of flexibility in the control system, allowing operators to intervene on-site and providing a seamless hardware channel for the "controller" described in claim 10 to achieve fully automatic intelligent control.

[0181] 2. Safety interlock and protection unit: Figure 5 It integrates key security logic, directly supporting the "security threshold judgment and interlocking protection" described in the method.

[0182] Oil temperature overheat protection: The "oil temperature overheat" alarm output contact of the temperature controller (XMT1, XMT2) (marked " / 5.9 Oil temperature overheat operation" in the diagram) is connected in series in the control circuit. Once the oil temperature exceeds the safety threshold, this contact will immediately open, forcibly stopping the heater or oil pump regardless of whether it is currently in manual or automatic mode. This achieves hardware emergency protection, and its reliability is far higher than that of pure software judgment.

[0183] Status feedback and indication: The operating status of each loop (such as the "fueling assist" indicator light) is not only displayed, but its signal can also be collected and fed back to the controller, becoming part of the "multi-source observation and health characterization data" for the system's comprehensive decision-making.

[0184] 3. Integration with intelligent control systems: The diagram clearly marks the interface terminals for connecting to the controller (e.g., "-EMG13", "-EMG14", etc.). These terminals clearly define the physical locations of the controller's outputs (DO) and inputs (DI).

[0185] Controller Output (DO): The relay coil is used to drive commands such as "start main oil pump", "stop main oil pump", "start heating", and "stop heating". It is the final execution output of the controller to perform intelligent decisions such as "cold and heat coordinated scheduling" and "dual pump switching".

[0186] Controller Input (DI): Used to receive feedback signals such as "oil temperature too high" and "running / stopping status". It is the original data source for the "multi-source data acquisition module" to sense the field status, perform health scoring and predictive maintenance.

[0187] This control interface embodiment demonstrates that the intelligent control system described in this invention perfectly integrates the high reliability of traditional relay control with the advanced features of modern computer control. Figure 5 The circuit shown is responsible for ensuring the safety and availability of basic operations, while the advanced controller of this invention performs data fusion, intelligent analysis and optimized scheduling on this basis. The two work together to form an optimal control system that is both safe and reliable as well as intelligent and efficient.

[0188] Figure 6This diagram illustrates the principle of temperature monitoring and safety interlock protection for a cone crusher control system, as provided in this application embodiment. Independent of software algorithms, it constructs a hardware-based, highly reliable safety protection barrier, specifically achieving limit protection for the inlet and outlet temperatures of the lubrication system, as well as direct interlock control of the outlet oil status.

[0189] See Figure 6 The circuit includes an inlet oil temperature controller (XMT1), an outlet oil temperature controller (XMT2), a level relay, an intermediate relay (KA4), and corresponding indicator and control terminals.

[0190] Its core protection logic and working mechanism are as follows:

[0191] Oil inlet over-temperature hard protection unit: Oil inlet temperature controller (XMT1, installed on the oil inlet line) monitors the lubricating oil temperature in real time. As described in step S200 of the instruction manual, although the system uses an algorithm to predict and schedule oil temperature, Figure 6 This provides the ultimate hardware protection. When the oil inlet temperature exceeds the maximum safety threshold, the XMT1's "over-temperature shutdown" alarm output contact (clearly marked "Return Oil XMT1 Over-temperature Shutdown" in the diagram) will activate immediately. This contact is connected in series in the system's main control circuit or main motor starting circuit (not fully shown in the diagram, but it is a standard design in this field). Its physical disconnection will directly cause the equipment to shut down, thereby absolutely ensuring that the equipment will not operate under over-temperature conditions and effectively preventing serious accidents such as bearing burnout.

[0192] Oil return status monitoring and interlocking unit: The oil return temperature controller (XMT2) is also equipped with an over-temperature alarm contact. More importantly, this circuit integrates monitoring of the oil return status:

[0193] As detailed in the text in the diagram: "When the oil return is normal, 1 and 3 are disconnected, 2 and 7 are energized, 6 and 8 are normally open and closed, and KA4 is working."

[0194] The contact state of the liquid level relay directly reflects the real-time status of the return oil level. When the return oil is normal, its internal contacts activate (6 and 8 close), driving the coil of the intermediate relay KA4 to be energized and engaged.

[0195] The contacts of KA4 can be used for two main functions: First, as a "normal liquid level" status signal, it feeds back to the digital input (DI) module of the controller, providing a key direct observation data for the health rating model; Second, its normally open contacts can be directly connected in series into the interlocking circuit that allows the equipment to start, realizing the hardware safety interlock of "no start without oil return", specifically supporting the protection action after the "consistency judgment of liquid level and oil return dual channels" as described in claim 1.

[0196] This safety protection embodiment demonstrates that the control system of the present invention employs a dual safety architecture of "software intelligent early warning + hardware absolute protection." Intelligent algorithms (such as health scoring) are responsible for early, flexible trend prediction and scheduling adjustments; while... Figure 6 The hardware circuitry shown is responsible for executing the final and most reliable power-off protection when parameters approach or reach unacceptable physical limits. Together, they form a comprehensive safety protection system that is both intelligent and absolutely safe, greatly enhancing the inherent safety level of the equipment.

[0197] Figure 7 This application provides a wiring diagram for a cone crusher control system assembly. As the core power supply framework and actuator drive overview of the control system, it integrates power distribution, short-circuit protection, and multi-source signal interfaces, providing a global, modular hardware implementation platform for the control methods of the aforementioned embodiments.

[0198] See Figure 7 The system's electrical architecture is powered by a three-phase power supply (L1, L2, L3), introduced through a main circuit breaker (QF1, 630A), providing overcurrent and short-circuit protection for each functional module. Its core components and connections are as follows:

[0199] Modular power distribution unit: After the main power supply passes through QF1, it is distributed to multiple independent branch circuit breakers (QF2 to QF7, all 32A). Each branch circuit breaker is dedicated to protecting a specific functional unit, forming a clear modular structure.

[0200] Main shaft drive module: Powered by the QF2 branch, it drives the main motor (185KW / 220KW) via contactor KM1. This module is the core power unit for performing crushing operations, and its start and stop are controlled by the output commands of the controller of this invention.

[0201] The lubrication system module includes two independent oil pump branches (QF3 and QF4), which control the #1 and #2 oil pump motors respectively via contactors KM2 and KM3. This physical redundancy design is the hardware foundation for realizing the "one-in-use, one-on-standby dual-pump lubrication unit" and the "intelligent switching between main and standby pumps" function.

[0202] Temperature control module: This module includes a heating branch (QF5), a refrigeration compressor branch (QF6), and a cooling fan branch (QF7), which are controlled by contactors KM4, KM5, and KM6 respectively. These three independent actuators are the direct operational objects for the controller to implement the "coordinated cooling and heating scheduling" algorithm, precisely managing oil temperature to optimize viscosity.

[0203] Multi-source data acquisition interface unit: Figure 7The area marked below is the "cabinet-out wiring terminal" area (X201, X202, X203). These terminals define the physical connection points between the "multi-source data acquisition module" and the field sensors, and are the sensory nerve endings for the entire system to achieve data-driven intelligent control.

[0204] Temperature signal interface: Terminals (T1-T6) are used to connect return oil thermocouples, inlet oil temperature sensors, etc., to provide raw data for the "oil temperature prediction and viscosity estimation" model.

[0205] Switching and pressure signal interfaces: Terminals (58, 59, etc.) are used to connect return oil switches, oil pressure sensors, etc., to provide the system with key status information such as "liquid level status data" and "oil pressure data", which are the basis for realizing health scoring and safety interlock.

[0206] System Integration and Scalability: This assembly diagram illustrates the complete power flow path (U0 / V0 / W0 to U3 / V3 / W3) from the main power input to each final actuator, while also clearly defining the interfaces for all signal acquisition. This clear and modular design not only ensures the system's reliability and maintainability but also provides excellent scalability. For example, if a new monitoring sensor (such as a vibration sensor) needs to be added, it can be easily connected to the reserved terminal block; if a new actuator needs to be added, a branch can be added under the main circuit breaker. This provides ample hardware space for the continuous iteration and functional upgrades of the intelligent control algorithm.

[0207] This system assembly embodiment demonstrates that the data-driven intelligent control method described in this invention is built upon, for example, Figure 7 It is built upon a modular, industry-standard electrical architecture. It is not simply a collection of circuits, but rather an innovative and optimal configuration that combines traditional execution components with rich data acquisition interfaces. This provides powerful, reliable, and flexible hardware support for upper-level intelligent algorithms, ultimately achieving the invention's objectives of improving equipment reliability, optimizing production efficiency, and reducing energy consumption.

[0208] Figure 8 This application provides an embodiment of an input / output (I / O) interface definition and power distribution wiring diagram for a cone crusher control system. As the central physical connection hub between the control system and external devices (sensors, actuators), it standardizes the definition of all data acquisition and control signal interface terminals, serving as the concrete physical bridge for realizing the "multi-source data acquisition" and "actuator control" functions.

[0209] See Figure 8 The core of the system's connection interface is a multi-functional cabinet-mounted terminal block. This terminal block is clearly divided into different functional areas, and their definitions and connection methods are as follows:

[0210] Actuator power output interface: The left side of the terminal block (terminals 1-13) is specifically used to distribute power to each temperature control and lubrication actuator.

[0211] Temperature control actuator interface: Terminals (U0, V0, W0) provide three-phase power to the oil heater; terminals (U3, V3, W3) provide three-phase power to the cooler. These two interfaces are the final power output terminals for the controller to execute the "cooling and heating coordinated scheduling" command and actively intervene in the oil temperature.

[0212] Lubrication system actuator interface: Terminals (U1, V1, W1) and (U2, V2, W2) independently supply power to oil pump motor #1 and oil pump motor #2, respectively. This physical interface directly corresponds to the "dual-pump redundant lubrication unit with one pump in use and one in standby" described in the claims. The controller can realize the intelligent control strategy of "main pump and standby pump pressure boosting switching" by controlling the upstream contactors (KM2, KM3) connected to this interface.

[0213] Sensor signal input interface: The right side of the terminal block (terminals 14-25) is specifically designed for connecting various monitoring sensors and is the physical entry point of the "multi-source data acquisition module".

[0214] Temperature signal acquisition interface: Terminals (T1-T6) are used to connect the inlet thermocouple (T1), the return thermocouple (T2), and temperature sensors (T3-T6) at other key temperature measurement points. These terminals introduce analog temperature signals into the control system, providing the most direct and continuous data input for the "oil temperature prediction and viscosity estimation" model.

[0215] Digital signal acquisition interface: Terminals (58, 59) are used to connect devices such as return oil switches and pressure switches. These digital signals provide key discrete state information of the lubrication system (such as "whether there is return oil" and "whether the pressure has been reached"), which are important bases for the system to perform "consistency judgment of liquid level and return oil dual channels" and real-time health status assessment.

[0216] System Integration and Signal Flow: The diagram clearly illustrates the signal flow path. All sensor signals are collected via terminal blocks and then uniformly connected to the core control module (such as the I / O module of a PLC) located in the center. Conversely, commands issued by the control module are converted into power outputs via contactors (such as KM1, KM3), ultimately driving the main motor and other equipment. This standardized interface design ensures orderly wiring throughout the system, greatly improving the maintainability, scalability, and anti-interference capabilities of the equipment.

[0217] This interface definition embodiment demonstrates that the intelligent control system described in this invention achieves standardized and modular connections with a wide variety of complex field devices through a meticulously planned terminal block. It is not only a node for power distribution but also a hub for information exchange, providing a stable and reliable data source and control output for upper-level intelligent algorithms. This is a key guarantee for the reliable implementation of the data-driven control method in industrial fields.

Claims

1. A control method for a cone crusher, characterized in that, include: Multi-source observation and health characterization data are acquired, and sampling alignment, denoising, element extraction, and health score calculation are performed to obtain a health score. The data includes oil pressure, oil temperature, return oil status, liquid level status, main motor current and voltage, power factor, contactor status, main pump and standby pump pressure boosting stage markings, and ambient temperature and humidity data. Perform gated start-up and star-delta consistency release judgment, switchover timing configuration and execution, and switchover process consistency verification and evaluation to obtain switchover consistency identifier and switchover gap parameters; The system acquires switching gap parameters, performs oil temperature prediction control and short-term prediction of cooling and heating synergy, scheduling of heating and compressor, and viscosity correction and defrosting determination, generating viscosity estimation parameters and defrosting indicators. Based on viscosity estimation parameters, load soft measurement and anti-blocking machine coordinated load estimation, feeding and ore discharge control, and impact assessment are performed to generate impact index parameters. Perform consistency checks on the dual channels of liquid level return, consistency checks on graded yielding and guided reset, power limiting and frequency limiting control, and reset process configuration processing to generate a reset step sequence and anomaly classification code; Based on the reset step sequence, anomaly classification code, and switching gap parameters, remote diagnosis and parameter adaptive write-back fingerprint accumulation, maintenance strategy generation, and write-back process processing are performed to update gating parameters, switching parameters, and yield parameters.

2. The method according to claim 1, characterized in that, The process of acquiring multi-source observation and health characterization data, performing sampling alignment, denoising, feature extraction, and health score calculation to obtain a health score includes: Acquire multi-source observation and health characterization data, perform sampling alignment and denoising processing to obtain standardized data; Multi-source observation and health characterization elements are extracted from standardized data, and element extraction processing is performed to obtain element sequences. The health status of the element sequence is calculated and processed to generate a health status score.

3. The method according to claim 1, characterized in that, The process of performing gated start-up and star-delta consistency release judgment, handover timing configuration and execution, and handover process consistency verification and evaluation to obtain handover consistency identifier and handover gap parameters includes: Simultaneously read standardized data and health scores, perform gate activation and star-angle consistency release judgment processing, and obtain release instructions; Based on the release command and standardized data, the handover timing is configured and executed to obtain the handover control sequence; Based on the handover control sequence and standardized data, consistency verification and evaluation of the handover process are performed to obtain handover consistency identifiers and handover gap parameters.

4. The method according to claim 1, characterized in that, The process of acquiring switching gap parameters, performing oil temperature prediction control and short-term prediction of cooling and heating synergy, scheduling of heating and compressor, and viscosity correction and defrosting determination, and generating viscosity estimation parameters and defrosting indicators includes: Standardized data and switching gap parameters are acquired to perform oil temperature prediction control and short-term prediction of cold and heat synergy, and the prediction results are obtained. Configure oil temperature prediction control and cooling-heating synergy duty cycle based on the prediction results, perform heating and compressor scheduling, and obtain thermal control commands; The system performs oil temperature prediction control, cold and heat synergistic viscosity correction, and defrosting determination on thermal control commands, generating viscosity estimation parameters and defrosting indicators.

5. The method according to claim 1, characterized in that, The process of generating the shock index parameters specifically includes: Obtain standardized data and viscosity estimation parameters, perform load soft measurement and anti-stagnation combined load estimation to obtain load estimation parameters; Configure the load soft measurement and anti-blocking machine coordination curve from the load estimation parameters, and perform feed control and ore discharge control to obtain the linkage control sequence; The load soft measurement and anti-stagnation mechanism are used to conduct a coordinated impact assessment of the linkage control sequence, and impact index parameters are generated.

6. The method according to claim 1, characterized in that, The process of performing consistency checks on the dual-channel return oil level, graded yielding and guided reset, power limiting and frequency limiting control, and reset procedure configuration processing, and generating the reset step sequence and anomaly classification code specifically includes: Acquire standardized data, thermal control commands, load estimation parameters, and switching consistency indicators; confirm the consistency of the dual-channel oil return and the consistency of graded yielding and guided reset to obtain consistency results. Configure the consistency, graded yielding and guided reset yielding strategies for the dual-channel oil return of liquid level from the consistency results and impact index parameters, perform power limiting control and frequency limiting control, and obtain the abnormal grade code; Configure the reset process for the abnormal classification code, including consistency of the liquid level return dual channel, graded concession, and guided reset, and generate a reset step sequence.

7. The method according to claim 1, characterized in that, Based on the reset step sequence, anomaly classification code, and switching gap parameters, the process of remote diagnosis, parameter adaptive write-back fingerprint accumulation, maintenance strategy generation, and write-back process processing, updating gating parameters, switching parameters, and yield parameters specifically includes: Obtain the reset step sequence, abnormal classification code and switching gap parameters, perform remote diagnosis and parameter adaptive write-back fingerprint sedimentation to obtain fingerprint data; Configure remote diagnostic and parameter adaptive write-back maintenance strategies from fingerprint data, generate rotation and window limit strategies, and obtain parameter update sets; The parameter update set is used in the remote diagnostics and parameter adaptive write-back process to update the gating parameters, switching parameters, and yield parameters.

8. The method according to claim 1, characterized in that, The load estimation steps involving soft measurement and anti-sluggish operation include: Establish a time window corresponding to the current crushing cycle, and align the recent data of main motor current and power factor with the oil pressure sequence and return oil status sequence based on the most recent release record and switching record; The pressure fluctuations corresponding to the rising current of the main motor in the oil pressure timing sequence are segmented to distinguish between stable segments and abrupt segments. The pressure fluctuations are then confirmed by combining the oil return state sequence to determine whether they are triggered by changes in oil circuit damping.

9. The method according to claim 1, characterized in that, The process of load soft measurement and anti-sluggish machine coordinated load estimation also includes: The coupling segment between electromagnetic side load and mechanical side load is identified to infer the degree of ore inclusion in the crushing chamber; The correspondence between the multi-point sampling sequence of inlet and outlet oil temperatures and the viscosity estimation parameters is read, and the rheological characteristics of different temperature zones are mapped into corrections for oil pressure damping and bearing friction, so as to eliminate estimation deviations under the same operating conditions in cold and hot oil.

10. A cone crusher control system, applied to the method according to any one of claims 1-9, characterized in that, include: The health score module is used to acquire multi-source observation and health characterization data, perform sampling alignment, denoising, feature extraction and health score calculation to obtain a health score; The switching control module is used to perform gate start-up and star-delta consistency release judgment, switching timing configuration and execution, and switching process consistency verification and evaluation processing to obtain switching consistency identifier and switching gap parameters; The oil temperature and viscosity control module is used to acquire switching gap parameters, perform oil temperature prediction control and short-term prediction of cold and heat coordination, heating and compressor scheduling, as well as viscosity correction and defrosting judgment processing, and generate viscosity estimation parameters and defrosting indicators. The load estimation and control module is used to perform load soft measurement and anti-blocking machine coordinated load estimation based on viscosity estimation parameters. It identifies the frequency band by calculating the cross-spectral density and coherence coefficient of oil pressure and current. The feeding and discharge control adopts the model predictive control paradigm and configures the time series of the feed inverter frequency setting and the discharge port actuator stroke setting. The impact assessment processing calculates the normalized cross-correlation peak value of the control sequence and the rate of change of the load estimation parameters to generate the impact index parameter. The anomaly handling module is used to perform consistency verification of the dual channels of liquid level return, consistency verification of graded yielding and guided reset, power limiting and frequency limiting control, and reset process configuration processing, generating a reset step sequence and anomaly classification code; The remote diagnostics and maintenance module is used to perform remote diagnostics, parameter adaptive write-back fingerprinting, maintenance strategy generation, and write-back process processing based on reset step sequence, anomaly classification code, and switching gap parameters, and to update gating parameters, switching parameters, and yield parameters.

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