Intelligent energy-saving adaptive optimization control method for explosion-proof motor

Abstract

The invention discloses an intelligent energy-saving self-adaptive optimization control method for an explosion-proof motor, relates to the technical field of explosion-proof motor control, and constructs a safety and energy efficiency unified closed loop mechanism for dangerous places. The method comprises the following steps: constraining three red lines of a virtual mirror image preposed temperature grade upper limit, minimum holding pressure and replacement completion time, importing a strategy number, a parameter packet and firmware version drill, and outputting a safe temperature difference, replacement standard judgment and an executable boundary; generating a strategy security file, verifying and signing, correcting time and cancelling governance, and registering guarding parameters into a to-be-deployed file after checking an equipment identifier; writing into a read-only area in a limited execution manner, controlling according to boundary projection, preferentially reducing magnetic flux and then increasing ventilation, and returning to the previous edition when necessary; registering temperature, pressure, power, output and replacement time sequences in an evaluation window, generating correction suggestions and calibrating parameters, reconstructing boundary and constraint abstracts, supporting safe energy-saving closed-loop evolution, generating and updating constraint abstracts, and entering the next round of release and gray scale popularization.

Description

Technical Field

[0001] This invention relates to the field of explosion-proof motor control technology, specifically to an intelligent energy-saving adaptive optimization control method for explosion-proof motors. Background Technology

[0002] Hazardous locations such as petrochemical, fine chemical, natural gas processing, pharmaceutical solvent workshops, and grain and oil dust storage facilities generally use explosion-proof motors in conjunction with purging and positive pressure to maintain operation. The production process is characterized by frequent start-ups and shutdowns, load fluctuations, and the drift of ambient temperature and humidity and the intensity of flammable medium leakage with shifts and seasons.

[0003] Existing control systems are mostly based on fixed interlocks and experience-based tuning: start-stop sequences and several thresholds are set in distributed control systems or programmable controllers, and release is based on conventional temperature, pressure and displacement time interlocks. Energy efficiency optimization is mostly limited to open-loop correction of given magnetic flux or air volume. The few systems that introduce digital twins are mostly used for process capacity assessment rather than intrinsic safety constraints. The common shortcomings are as follows: First, safety clauses are not established as hard boundaries in advance, and post-event judgments are often used instead of pre-event exclusions, making it impossible to prove before going live that the policy will not touch the red lines of temperature level limits, minimum holding pressure, and replacement completion time. Second, policy distribution lacks strong binding of source signatures, integrity verification values, and device compatibility consistency, making it easy for replays or version rollbacks to occur when the revocation list is updated late. Third, during the execution period, the policy is directly issued based on reference control, lacking online protection of restricted execution and executable boundaries, failing to translate the shrinkage of the safe temperature difference into priority actions of reducing magnetic flux targets or increasing ventilation volume, and lacking a smooth channel to roll back to the previous version of the policy. Fourth, post-operation evaluations are mostly based on coarse-grained energy consumption comparisons, lacking time registration with the virtual baseline and multi-channel joint criteria, resulting in a distorted trade-off between energy saving and safety, making it difficult to accumulate into a constraint summary and policy security file that can be reused in the next round, and thus making the release of whitelists and revocation lists lack risk intensity-driven rhythm governance.

[0004] Faced with the above complex operating conditions, when starting up during shift changes or switching processes, ventilation conditions change due to filter blockage or sudden increase in air duct resistance. If only fixed thresholds and offline verification are relied upon, the reference control may cause the outer surface temperature to rapidly approach the upper limit of the temperature level or cause the housing pressure to drop below the minimum holding pressure during short-term overshoot. During remote maintenance or batch deployment, if the policy number, parameter package, and firmware version are not strongly bound to the device identifier, the old version may be re-released to incompatible devices due to network caching or human error, and the protection parameters cannot become the only mandatory input during the execution period. In the case of load fluctuation and environmental leakage during operation, if there is a lack of minimum disturbance projection based on the executable boundary and the priority order of "reduce magnetic flux first, then increase ventilation", the controller cannot immediately convert the safe temperature difference contraction into a compliant action, resulting in either touching the boundary and forming an inherent safety hazard, or being overly conservative and wasting energy efficiency. In the post-event evaluation stage, if the real trajectory and virtual baseline are not rigorously time-registered and jointly judged by multiple channels, the energy-saving conclusion may be misled by occasional operating conditions or measurement noise, further affecting the decision on the direction of parameter calibration and the release rhythm, thereby amplifying the exposure during the gray-scale diffusion stage. Summary of the Invention

[0005] (a) Technical problems to be solved To address the shortcomings of existing technologies, this invention provides an intelligent energy-saving adaptive optimization control method for explosion-proof motors. It constructs a closed-loop mechanism that unifies safety and energy efficiency for hazardous locations. Using a constrained virtual mirror with three red lines—upper limit temperature level, minimum holding pressure, and replacement completion time—it imports strategy numbers, parameter packages, and firmware version simulations, outputting safe temperature difference, replacement compliance judgments, and executable boundaries. It generates a strategy safety file, verifies its signature, synchronizes time, and reverts its management. After verifying the equipment identification, it registers the protection parameters for deployment. Restricted execution is written to a read-only area, controlled by boundary projection, prioritizing flux reduction followed by ventilation increase, and reverting to the previous version when necessary. In the evaluation window, it registers temperature, pressure, power, output, and replacement timing, generates correction suggestions and calibrates parameters, reconstructs boundaries and constraint summaries, supports the evolution of the safety and energy-saving closed loop, and generates updated constraint summaries for the next round of release and gray-scale rollout. This solves the technical problems described in the background art.

[0006] (II) Technical Solution To achieve the above objectives, the present invention provides the following technical solution: An intelligent energy-saving adaptive optimization control method for explosion-proof motors includes: constructing a virtual mirror, setting the upper limit of temperature level, minimum holding pressure, and replacement completion time as hard constraints; importing strategy number, parameter package, and firmware version for simulation, generating safe temperature difference, replacement compliance judgment and executable boundary, and outputting candidate list and constraint summary; A policy security profile is generated for the candidate list, including source signature, integrity check value, firmware version and device compatibility; the signature and timestamp are verified, and the invalidation is blocked according to the revocation list; those that pass the verification and have consistent device identifiers are put into deployment, and the three constraints are registered as protection parameters; Enable restricted execution, write the guardian parameters to the read-only area and bind them to the file; control the executable boundary projection according to the statement; disable startup if the replacement fails to meet the standard or the pressure is lower than the minimum holding pressure; reduce magnetic flux and increase ventilation when the temperature approaches the upper limit; if not feasible, revert to the previous version; The system summarizes temperature, pressure, input power, output, and displacement timing within a specified window, aligns it with the virtual mirror baseline, and calculates the metrics. When deviations exceed limits, it generates correction suggestions, updates parameters, and reconstructs the executable boundary and constraint summary. It also adjusts the whitelist and revocation list based on vulnerability notifications.

[0007] Furthermore, the virtual image adopts a three-domain coupled modeling of device, environment and safety clauses. The state includes external surface temperature, shell pressure and combustible volume fraction. The control input includes ventilation volume and magnetic flux target. The three hard constraints are embedded in the form of obstacles. The executable boundary is fixed in the constraint summary as polyhedral parameters. The boundary parameters are generated by perturbation scanning and operating condition layering. The parameters are stored in a one-to-one association with the index of the parameter package and the policy number.

[0008] Furthermore, a replacement compliance determination is constructed by the evolution of replacement dose and concentration, and the safe temperature difference and pressure margin are calculated within the exercise time window. Based on the conditions that the replacement compliance determination is true, the safe temperature difference is not lower than the threshold, and the executable boundary is not empty, the candidate list is generated and the corresponding constraint summary is recorded. The exercise sequence includes the actual start-up and shutdown sequence and ventilation linkage mapping, and the entry number is saved in the mirror database.

[0009] Furthermore, the policy security profile uses structured message sequence to bind the constraint summary, the policy number, the firmware version, and the device identifier, and introduces domain tags to generate integrity verification values; The system combines time stamping, membership verification, and log root writing. The revocation list adopts a verifiable set structure for subsequent verification calls, and generates signatures through forward secure key chain evolution and archives them on the platform side.

[0010] Furthermore, a joint admission criterion is set in the platform-to-controller link, including signature verification result, log membership, latency window and the revocation list status; The device identifier consistency and rollback conditions are further filtered to generate the set to be deployed. The device side uses a key to form write evidence for the guardian parameters, the policy number and the firmware version, and records the reason code and time stamp and sends it back to the platform.

[0011] Furthermore, upon going online, the written evidence is read, the guardian parameters are fixed in the read-only area, and a permission index is constructed that includes the replacement compliance determination, the shell pressure is not lower than the minimum holding pressure, and the initial configuration falls within the executable boundary; when the permission is granted, the reference control is safely projected to generate the implementation control, otherwise the loading is aborted and the rejection classification and rejection source are output.

[0012] Furthermore, during operation, a priority order is adopted to first reduce the magnetic flux target and then increase the ventilation volume, and the implementation control is continuously updated by combining short field-of-view sequence projection and control rate limiting; When it is not feasible within a continuous window and the relaxation metric exceeds the threshold, the previous version of the strategy is selected and the switch is smoothly performed by the interpolation factor. At the same time, a switch event summary is generated, signed and filed, and the switch count and the most recent effective batch number are recorded in the controller's read-only area.

[0013] Furthermore, within the agreed evaluation window, the outer surface temperature, shell pressure, input power, output and replacement timing are reliably assembled and aligned with the virtual mirror baseline through time registration; A joint criterion is constructed for unit output energy consumption, temperature, pressure, and displacement time. When the deviation exceeds the threshold, the aforementioned correction suggestion is generated and the calibration process is initiated. The evaluation data adopts a unified sampling rate and time-scaled calibration strategy and retains the registration parameter set.

[0014] Furthermore, the parameters such as heat loss, heat dissipation, effective volume and leakage are calibrated within the physically feasible region using Bregman divergence and proximal canonicalization, the executable boundary is reconstructed and the constraint summary is updated, and the updated strategy number is output. The whitelist and the revocation list are adjusted synchronously based on the risk intensity and release rhythm factor, and the parameter change history and calibration iteration number are retained for subsequent retrieval.

[0015] Furthermore, the grayscale release orchestration is based on the release rhythm factor, equipment risk weight, operating condition similarity, and minimum margin of temperature and pressure to calculate the equipment allocation probability; Within a batch, the joint score and relaxation metric of the device side are continuously statistically analyzed, and the data is frozen or incrementally released according to the stop indication. After aggregating the running evidence, the archive is merged and an updated constraint summary is generated as the sole entry point for the next round of virtual image verification, and the batch topology is archived on the platform.

[0016] (III) Beneficial Effects This invention provides an intelligent energy-saving adaptive optimization control method for explosion-proof motors, which has the following beneficial effects: The model is hard-embedded with three red lines: upper limit of temperature level, minimum holding pressure, and replacement completion time. Combined with start-up and shutdown sequence, ventilation linkage and magnetic flux target to generate safe temperature difference, replacement compliance judgment and executable boundary, non-compliant strategies are eliminated in advance to form a candidate list and constraint summary, thereby reducing trial and error at the source and locking subsequent calculations within the provable safety domain.

[0017] By using policy security profiles to strongly bind source signatures, integrity check values, firmware versions, device compatibility, and timestamps, and by overlaying revocation lists and device identifier consistency verification during the transmission and loading phase, a set to be deployed and written evidence are generated, making the guardian parameters the only mandatory input when going online, systematically eliminating the risks of cross-device replay and version rollback.

[0018] Upon deployment, restricted execution mode is enabled, and the guardian parameters are written to the read-only area and bound to the policy security file. Reference control is implemented through minimum disturbance projection. During operation, the safety temperature difference and pressure margin are continuously evaluated, and adaptive adjustment is made according to the priority of "first reduce magnetic flux, then increase ventilation". If there is still no improvement, it is smoothly rolled back to the previous version of the policy to ensure that performance optimization does not exceed the boundary.

[0019] Post-run evaluation aligns the real trajectory with the virtual baseline through time registration. The joint criterion is based on energy consumption per unit output and entropy margin. If the deviation exceeds the limit, a correction suggestion is generated. The heat loss and heat dissipation estimation parameters are constrained and calibrated using Bregman divergence and near-end regularization. Then, the executable boundary and constraint summary are reconstructed to provide a reliable entry point for the next round of verification.

[0020] The whitelist and revocation list are dynamically adjusted based on the improved joint score and risk intensity. The release rhythm factor controls the gray-scale diffusion speed, and quotas are allocated to equipment according to the similarity of working conditions and local margin. This balances promotion efficiency and exposure control, and supports the strategy to move quickly and steadily within the safety barrier.

[0021] Constraint summary, policy security profile, written evidence, and audit log are integrated throughout the four steps, and any policy decision can be traced back to the policy number and firmware version; virtual image, trusted release, restricted execution, and canary release reinforce each other, realizing a closed-loop unity from modeling, release, execution, evaluation to re-verification. Attached Figure Description

[0022] Figure 1 This is a schematic diagram of the intelligent energy-saving adaptive optimization control method for explosion-proof motors according to the present invention. Detailed Implementation

[0023] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0024] Please see Figure 1 This invention provides an intelligent energy-saving adaptive optimization control method for explosion-proof motors, comprising: To address the inherent tension between energy efficiency optimization and intrinsic safety of explosion-proof motors operating in hazardous locations, a constrained virtual mirror verification mechanism is proposed, which completes hard constraint closure and strategy optimization in a virtual-real fusion manner before online execution.

[0025] Step 1: Before going live, use a constrained virtual image to verify that the three hard constraints of the upper limit of temperature level, minimum holding pressure, and replacement completion time are written into the mechanism model. Import the strategy number, parameter package and firmware version and conduct a ventilation linkage exercise in the start-stop sequence to generate safe temperature difference, replacement compliance judgment and executable boundary. Remove non-compliant items and condense the constraint summary as the unique input anchor point for the entire subsequent link. Solidify the working condition label and simulation configuration to support reproduction and traceability. Step 101: Construct a virtual image based on the coupling of the three domains of device, environment and safety clauses, and hard-embed the three protection parameters in a barrier manner to ensure that any subsequent simulation is carried out in the provably safe domain. In order to avoid the lag of calculating and blocking after treating the safety clauses as a post-hoc judgment, the clauses are hard-embedded at the virtual image layer, so that the device mechanism, environmental disturbances and clause boundaries are compatible in the same state space.

[0026] Specifically, a state vector is constructed that includes the external surface thermal state and the shell pressure. Control inputs driven by ventilation and magnetic flux And form a parameter cluster with environment set and policy parameters. Based on this, the obstacle potential is defined. As an immediate reaction of the terms to the state evolution, and entering the dynamic equation as a gradient term, it achieves feedforward repulsion of the boundary.

[0027] The master equation of dynamics is expressed as: Where: state vector Includes external surface temperature Casing pressure Continuous states, with values ​​taken from the physical domains allowed by the device; Control input Includes ventilation volume With flux target The value is determined by the strategy number. parameter package limited; Strategy parameter package : with strategy number The calibration parameter vectors correspond one-to-one, and their values ​​are taken from the allowed range in the strategy configuration library; Environmental parameter vector Includes ambient temperature External conditions such as background combustible gas levels are taken as values ​​for the on-site calibration domain. Obstacle potential : Connecting to the guardian parameter group The convex potential function takes non-negative values; Guardian parameter group : These are the upper limits of the temperature levels. Minimum holding pressure Upper limit of replacement completion time The value is determined by safety regulations; vector field , : These represent the mechanism evolution of accessibility and the obstacle coupling weights, respectively, with values ​​determined by mechanism modeling and parameter identification; To demonstrate the coupled memory of the equipment's heat-fluid-magnetic properties, the external surface temperature... Energy cost structure using memory kernel convolution: Where: ambient temperature : The baseline temperature of the on-site environment, the value of which is determined by the scene; thermonuclear amplitude : Convolution kernel amplitude coefficient, with positive values; thermal time constant : Thermal response decay timescale, with a positive value; heat source coefficient : Magnetic flux heating intensity coefficient, with a positive value; heat dissipation coefficient Ventilation heat dissipation intensity coefficient, with a positive value; ventilation nonlinearity index. The nonlinear index of ventilation efficiency, with a value greater than or equal to 1; Magnetic flux target Ventilation volume The control trajectory over time, with values ​​determined by the strategy parameter package. Equipment limit constraints; external surface temperature The predicted outer surface temperature from the mirror image must not exceed the upper limit of the temperature class. ; To explicitly incorporate the clause boundaries into the evolution, a logarithmic barrier is constructed for the upper limit of the temperature range minus the minimum holding pressure: Where: obstacle weight The boundary sensitivity is weighed separately for temperature and pressure, and a positive value is assigned. Temperature level upper limit Safety regulations specify an upper limit, which is positive; minimum holding pressure. Safety regulations specify a lower limit, which is taken as positive; shell pressure. The predicted internal pressure of the housing must be no less than the minimum holding pressure. ; External surface temperature : Same as the definition above; appears as the obstacle independent variable in this formula; Therefore, the aforementioned three-domain coupling and obstacle injection endow the virtual image with a natural self-protective property at the computational layer, which is immediately pushed away when it approaches the boundary. This suppresses out-of-bounds trajectories in the early stages of simulation, thereby saving unnecessary computational power for subsequent policy scanning. By injecting obstacle potentials at the dynamics layer, a safe priori understanding of the terms and mechanisms is achieved, ensuring that any subsequent energy efficiency adjustments are performed within a provably safe manifold.

[0028] Temperature and pressure constraints alone are insufficient to determine the completion rate of flammable medium replacement. Therefore, an achievability metric of replacement dose integral-threshold cross-time is introduced to ensure an upper limit on the replacement completion time. The rigid standardization. First, based on volume fraction of combustible volume fraction. Constructing the substitution dose function: Where: effective volume : Equivalent spatial volume involved in the permutation, with a positive value; leakage coefficient External combustible gas leakage intensity coefficient, with a non-negative value; leakage nonlinearity index. : Characterizes the nonlinearity of leakage depending on concentration, with a value greater than or equal to 1; combustible volume fraction : The internal concentration trajectory predicted by mirror image, with values ​​of Dosage threshold : The cumulative dose threshold required to achieve a qualified replacement, with a positive value; replacement completion time prediction. The time it takes for the dose function to first cross the threshold; For closed-loop concentration kinetics, concentration evolution adopts a leakage-displacement coupling form: In the formula: represents the coefficient of the substitution term. Effective volume. Same as before; in this formula, the standard replacement strength is specified. Leakage coefficient. Leakage nonlinear index Same as before; constitutes an external disturbance in this formula.

[0029] Therefore, the criteria for replacement are defined. : Where: Displacement compliance determination Boolean index, with values... Achieving the target is 1, exceeding the time limit is 0. Predicted replacement completion time. Time limit Same as above; Thus, the closure of permutation reachability makes the three guardian parameters... It is executed as a single simulation, providing a complete signal for subsequent boundary calculations. Through dose-time coupling and threshold crossing, substitution attainment is transformed into a computable time function, ensuring accuracy. The hard constraints are verifiable and repeatable.

[0030] Step 102: Under the sequence consistency constraint of start-stop-ventilation-magnetic flux, complete the strategy exercise, boundary calculation and candidate list generation, and output a reusable constraint summary; Based on the requirements of conducting drills according to the actual start-up and shutdown sequence, ventilation linkage, and changes in magnetic flux targets, an event sequence was constructed. Drive control input to control input The segmented evolution maintains sequence consistency in the time domain through a hybrid event system.

[0031] For each operating range, the three trajectories of heat, pressure, and concentration are mirrored back, and the safe temperature difference for online access is calculated. Define heat margin: Where: safety temperature difference Temperature margin scalar, can take positive or negative values; Simulation time domain length The upper limit of the time window for this exercise, with a positive value; the range of extreme values ​​is limited. External surface temperature. Same as before; find the maximum value in this formula.

[0032] Simultaneously, a unified boundary measure is formed using minimum pressure margin and displacement time: Where: Boundary margin Strategy Number The minimum margin scalar, which can take positive or negative values; Therefore, if the boundary margin Then immediately determine the strategy number. It lacks the feasibility of going live; thus avoiding meaningless and unreliable deployment processes for non-compliant strategies in subsequent stages, thereby shortening the turnaround time of the project closure.

[0033] It is worth emphasizing that the above-mentioned sequence consistency accurately reproduces the superposition effect of start-stop waveforms, ventilation distribution, and magnetic flux waveforms, avoiding optimistic biases caused by evaluating the three actions separately. A unified margin measure is used across temperature, pressure, and displacement, allowing the three types of risks under the sequence to be compared and adjudicated on the same scale.

[0034] To avoid vulnerable passage under a single operating condition, the environmental parameter vector is... A set-based scan is performed to construct a robust, executable boundary and output a portable polyhedral approximation for rapid comparison in subsequent steps. First, a perturbation scenario is defined. Risk functional under: Where: risk functional In the initial state With disturbance The most unfavorable boundary overflow range, which can take positive or negative values; initial state : The initial state vector of the simulation, taking values ​​from the operating domain; the set of perturbations. : A Cartesian product set including ambient temperature, external leakage, duct resistance, etc., with values ​​set to a preset safety assessment domain; external surface temperature Casing pressure Predicted replacement completion time : In disturbance The mirrored output below takes the same values ​​as before; Based on this definition, robust executable boundaries are established. To satisfy the initial domain for all perturbations: Where: Executable boundary : In the perturbation set The set of initial states that remain within bounds is a subset of the state space; to facilitate rapid comparison and signature fixing in subsequent stages, the executable boundary is output as a polyhedron: Where: boundary parameter vector : Determined by the allowable peak value of magnetic flux With minimum ventilation supply The composition and values ​​are determined by device limits and the policy library; polyhedral matrix Polyhedral vectors : Define a family of half-spaces with approximate boundaries, whose values ​​are obtained by fitting within the samples; Approximate boundary Real Boundaries : These are the linear approximation and exact definition of the executable boundary, respectively; Ultimately, the overall safe temperature difference Replacement standard determination With the executable boundary Generate a candidate list: Where: Candidate list The set of strategy IDs verified takes the value of the complete set of strategies. A subset of [the policy] will be used for subsequent trusted releases; the complete policy set [is also included]. : The set of all evaluable strategy numbers; temperature difference buffer : A conservative buffer for safe temperature difference, whose value is non-negative; To ensure traceability and portability, a constraint summary is constructed. As a minimal sufficient description of cross-step carrying: Where: constraint summary : A structured tuple used for cross-stage references, whose values ​​are combinations of the above elements; Firmware version : with strategy number The bound firmware version identifier, whose value comes from the firmware library; By using perturbation scanning and polyhedral signatures, complex security domains are compressed into structured digests that are publishable, verifiable, and rollbackable, providing a minimum sufficient set for comparison for subsequent trusted releases.

[0035] Through state vector + Control Input + Parameter Cluster The three-domain coupling mirrors respond to the temporal consistency of start-stop sequence, ventilation linkage, and magnetic flux target changes, and maintain boundary margins on a single scale. Complete compliance rulings; and then use the perturbation set Robust scan construction of executable boundaries , with polyhedron Provide a portable signature, forming a safe temperature difference. Replacement standard determination Constraint Summary .

[0036] In hazardous locations, candidate list If the strategy is not verified by a trusted publishing link and identity integrity, any energy-saving benefits may be offset by key forgery, version rollback or path pollution, thereby inducing systemic risks of out-of-bounds execution, hysteresis protection and untraceability.

[0037] Step 2: Focusing on trusted publishing and identity integrity, generate a policy security profile for each policy number in the candidate list, sequentially bind constraint summary, firmware version and device identifier, and verify signature and time synchronization. Combined with the revocation list, block invalid entries in real time. Devices with the same identifier are added to the deployment set. At the same time, the upper limit of temperature level, minimum holding pressure and replacement completion time are registered as online protection parameters. All fields are concatenated in a fixed order to form a structured message for backup.

[0038] Step 201: Targeting the Candidate List Each strategy number Generate policy security profile and constraint summary Guardian parameter group Firmware version Equipment identification By binding content and anchoring it to time, a verifiable source and integrity baseline can be established; Once a candidate strategy enters the release chain, without standardized formatting and signature domain isolation, it is highly susceptible to issues such as delayed implementation, bypassing revocation, and other vulnerabilities caused by replaying different content with the same name across devices. Therefore, it is necessary to use domain tags. Data domains for different purposes are strictly isolated and summarized using a one-time summary value. For structured messages Given an irreversible mapping; further, a forward-secure key chain. Abstract and time stamp Simultaneous signing enhances resistance to rollback and replay. Therefore, it revolves around a single chain of content binding, time anchoring, and forward key security, thereby eliminating sources of uncertainty during the file generation stage.

[0039] To ensure that no structural ambiguity occurs during the cross-process transfer of documents, the constituent elements are first sequentially linked, and fields with different purposes are isolated by field labels to form a unique structured message. .

[0040] Then on Applying a domain-separating hash operator yields a policy integrity check value. As the sole anchor for subsequent signatures and log entries into the chain, the formula is as follows:

[0041] Where: structured message : Constraint summary Strategy Number Firmware version Equipment identification Domain tags Guardian parameter group The byte sequence concatenated in normal order; its value is a finite string of bytes; Constraint Summary :Include Values ​​can be a set of fixed-length or variable-length fields; strategy number. A globally unique identifier for a strategy; its value comes from the entire set of strategies. Firmware version : Firmware identifier compatible with the policy; value taken from firmware library; device identifier : The unique hardware identifier of the target controller; the value is the result of reading the security element on the device side; domain label : Field separation flag; value is a fixed-length byte string; Guardian parameter group Temperature level upper limit Minimum holding pressure Upper limit of replacement completion time The triplet; its value is determined by security specifications and field calibration; domain-separated hash. : Irreversible digest function with domain labels; outputs values ​​of fixed length; provides collision resistance and anti-image protection.

[0042] Therefore, structured messages Uniqueness and Summary Value The irreversibility of these factors together ensures the semantic stability of the archive content during cross-system transmission, thus providing a clear recipient for subsequent signing and log insertion. The data from step one... With Guardian Parameters Direct embedding This ensures that any subsequent modifications will be made within [the specified timeframe]. The window is explicitly exposed to prevent attacks from being made without leaving a trace through minor modifications.

[0043] If a static signature key is used, once the key is leaked, older versions can be replayed indefinitely. Therefore, forward-secure key evolution is introduced, along with time stamping. Directly incorporate into the signature, combined with a verifiable log root. Achieve dual timing anchoring. Specifically: Where: private key sequence Forward-secure private key chain Period value; the value is taken from a random seed in space through unidirectional evolution; One-way evolution function : Resilient key evolution function; values ​​are spatial mappings; time stamps : A timestamp generated by a trusted time source; its value is a monotonically increasing time code; connector Unambiguous byte-level concatenation; values ​​are operators; signature value :right The digital signature; the value can be either a curve or a lattice-based signature output; To support traceable auditing, signature entries are also written to a verifiable log, forming a rolling root: Where: log root : No. Verifiable log root for a given period; values ​​are fixed-length digests; aggregation mapping. Aggregate operators that satisfy verifiable membership relations (such as Merkle type) take values ​​as deterministic functions; previous root : Root of last period's log; value is the same as above; forms a chain evolution; Therefore, every archival entry carries and The dual authentication mechanism allows for both public key verification of the signature and member proof verification of its inclusion in the log and its lack of tampering or rollback. The combination of forward security and time anchoring renders replay and delayed delivery ineffective on both the cryptographic and log sides, creating a structural redundancy that counters rollback.

[0044] Step 202: In the transmission and loading link from the platform to the controller, implement step-by-step verification, cancel immediate blocking, and compare device identifier consistency, and then transfer the guardian parameter group. Registration is the only mandatory input during the deployment phase, ultimately generating a set to be deployed. .

[0045] Even if the generated archive is reliable, replay, replacement, and cross-device forwarding can still occur in the process; furthermore, if the revocation list is not queried in a timely manner, known invalid entries may still be incorrectly accepted. Therefore, it is necessary to construct a joint admission criterion that covers signature verification, log membership, time windows, revocation status, and device consistency. And will be determined by the strategy number of the criterion. Converging to the set to be deployed At the same time, leave evidence written to the device side. For audit purposes.

[0046] To avoid each segment of the link verifying only half of the data, all necessary conditions are combined into a single computable acceptance function, and a transmission delay window is introduced to prevent late packets from masquerading as valid, resulting in the following joint criterion: Where: Receive time stamp : The local time the controller receives the file; the value is a monotonic count value; Delay window : The time delay from message issuance to receipt; the value is non-negative; threshold : Maximum acceptable latency; value set by operation and maintenance strategy; signature verification operator Using public key For signature With message The verification result; the value is boolean; public key : with private key The paired public key; its value is fixed in the trusted distribution. Member verification Use membership proof verify Is it included in the log root? The value is Boolean; membership proof :right Log member proof; values ​​can be fixed or variable length proof objects; revocation predicate :judge Does it appear on the revocation list? The value is Boolean. Cancellation List : A set of revocations continuously maintained by the platform; its values ​​are verifiable set structures; joint criterion Acceptance criteria after considering all factors; the value is... Indicator functions Numerical representation of logical conditions; values ​​are... ; Therefore, any file that fails to meet any condition will be rejected at the current stage and a reason code will be recorded, avoiding unnecessary attempts to load first and then roll back. By merging signature verification, membership, latency, and revocation into a single point of decision, implementation ambiguity and sequence dependencies are reduced, forming a portable admission logic.

[0047] Even if the file is authentic, it is essential to ensure that the target device is consistent and that the protection parameters are the only mandatory input during the deployment period. Otherwise, there is a risk of incorrect deployment across devices and bypassing the protection during the deployment period.

[0048] In passing Subsequently, device consistency predicates and rollback registrations are introduced to form the final set to be deployed. And generate device-side write evidence. For future verification. First, define the device consistency predicate: Among them, equipment identification The target identifier bound to the file, the actual measured identifier on the device side. Read by the security element; Values It is used to block cross-device delivery.

[0049] To prevent rollback, define version number mapping and counting constraints: Where: Equipment side identification : Hardware identifier returned by the controller's safety element; value is read-only; consistency predicate The result of determining the consistency of equipment identification; the value is... ;counter The old and new values ​​of the monotonic count on the equipment side; the value is a strictly monotonic count. Version mapping : Firmware version Compared to the current version The difference after mapping to the ordered field; the value is an integer; inverse rollback predicate. : Simultaneously satisfies the criteria of increasing count and non-decreasing version; the value is Device key : Device-side signature private key residing in the secure element; value is read-only; write evidence :right The device-side signature; its value is the signature object; Based on this, the final set to be deployed is defined as follows: Where: the set to be deployed : A set of strategy IDs that have passed all admission criteria and completed registration; the value is... A subset of; entering the restricted execution phase before going live.

[0050] Therefore, only when the archive passes the triple test of joint criteria, device consistency, and rollback and generates write evidence can it be considered valid. After that, the strategy number Only then can you enter. Meanwhile, the guardian parameter group It has been written to the read-only field and passed through This creates a verifiable, non-repudiable record, providing strict and unique mandatory input for the restricted execution and boundary protection in step three. Device consistency and rollback are written into formal mathematical criteria to avoid the loophole of prior signature at the implementation layer before device verification. The retention of these records provides crucial evidence for cross-period auditing and incident tracing.

[0051] Ultimately, evidence was written. Ensure the guardian parameter group This becomes the only mandatory input during the deployment phase. Therefore, the set to be deployed... It is no longer a product of reliance assumptions, but rather the result of verifiable evidence. Upon proceeding to step three, the controller can directly... and Startup is restricted; any deviations discovered during operation can be followed. Going back to the time of release and the responsible party. Upon entering step four, With log root This will be linked with on-site vulnerability announcements, dynamically adjusting the release and withdrawal schedules of whitelists to keep the exposure scope and release frequency under control. This forward-looking release-verification framework ensures that intrinsic safety is not compromised, while providing a verifiable and auditable operational foundation for the rapid evolution of energy efficiency strategies.

[0052] Step 3: In restricted execution and boundary protection, write the protection parameters into the read-only area and bind them to the policy security file. Based on the executable boundary, perform minimum disturbance projection on the reference control to generate implementation control. During operation, continuously monitor the external surface temperature, casing pressure and ventilation volume. First reduce the magnetic flux and then increase the ventilation. If it is not feasible in the short term, smoothly revert to the previous version of the policy to ensure that the control instructions are always constrained by the boundary. Critical events and control change records are recorded as audit entries and associated with the device identifier.

[0053] Step 301: Enable restricted execution immediately upon going live and complete the read-only guardian parameters. Writes a triple binding of policy, device, and boundary, and uses permission criteria to determine whether to enter runtime.

[0054] If the system is only manually checked at the moment of deployment, it is highly susceptible to scenarios that violate inherent safety, such as starting the machine before the replacement criteria are met and operating it under low pressure, only to rectify the situation later. Therefore, it is necessary to rely on the write evidence from step two. As the sole credential, the guardian parameter group Write to the read-only area and immediately verify the replacement criteria. With shell pressure Compliance; at the same time, using executable boundaries. The initial operating conditions are evaluated collectively, and a single permissible indicator is used to determine whether execution is allowed at a calculable threshold.

[0055] Therefore, the three-step coupling of read-only write, permission determination, and control pre-projection is first completed, and then the policy number is... Reference control Security mapping for implementing control .

[0056] Upon going live, the controller reads and writes evidence. and the guardian parameter group Solidify to a read-only region, then apply the initial state vector according to the candidate strategy. Calculate the licensing indicators. These indicators determine whether the replacement program meets the eligibility criteria. Casing pressure Combined with boundary executability into a single Boolean admission: Where: Permit Indicators The acceptance result at the moment of going live, with a value of Replacement standard determination : Is the permutation output in step one within the time limit? The instruction to complete within the time limit, with a value of ; Casing pressure The instantaneous casing pressure upon connection should not be lower than the minimum holding pressure. Minimum holding pressure : The stress threshold of the protection parameters, the value of which is set by the specification; boundary parameter vector The initial configuration for online deployment corresponds to the peak magnetic flux and lower bound of airflow, the values ​​of which are determined by the strategy parameter package. Given; and approximate boundary Perform set determination; Approximate boundary The polyhedral executable boundary output in step one takes the value of a family of half-spaces; indicator function. Numerical encapsulation of logical conditions, with values... ; Therefore, if the license indicator If so, the system will refuse to boot and the reason code will be recorded; Then, the process enters the pre-projection control phase. This allows for the merging of the three hard constraints with the executable boundary using a single permission metric, avoiding the hidden risk of failing each constraint individually but resulting in overall imbalance.

[0057] To ensure strategy numbering Reference control Control is implemented by generating a minimum disturbance projection without touching the boundary within one prediction step. : In the formula: Implement control The actual control output after projection is subject to constraints imposed by the constraint set. Reference control : From the strategy parameter package The generated expected control takes the value of the device's allowed domain; L2 norm. Euclidean metric, taking values ​​that are non-negative real numbers; used for temperature prediction. Based on the short-term temperature prediction using the dynamics of step one and current observations, the value should be lower than the upper limit of the temperature class. Buffering; predicting pressure Short-term pressure forecasts should be taken at values ​​higher than the minimum holding pressure. Buffer; buffer size : A conservative buffer between temperature and pressure, with non-negative values; time step The prediction step size of the control loop, which takes a positive value; Thus, control is implemented. The principle of minimizing deviation ensures immediate respect for the protected boundary; if the constraint is not feasible, the fallback and protection logic in step 302 is initiated. Through convex optimization projection, the energy efficiency strategy is translated into compliance control, making safety a primary constraint and performance an additional objective.

[0058] Step 302: During operation, monitor the safe temperature difference. With boundary margin Conduct online assessments and adjust magnetic flux targets according to priority. With ventilation And if it is not feasible, the previous version of the strategy will be triggered. Smooth rollback and audit solidification.

[0059] The non-stationarity of operating disturbances means that a single projection cannot guarantee safety throughout the entire timeframe. Therefore, it is necessary to measure online how close the device is to the boundary and determine the adjustment sequence of first reducing the magnetic flux and then increasing the airflow. If the safety margin cannot be restored in the short term, the previous strategy with a better safety margin must be selected. And a smooth transition is achieved to avoid transient risks caused by sudden changes in thermal-fluid coupling. Therefore, the approach revolves around a closed loop of margin assessment, priority adjustment, feasibility monitoring, and strategy rollback.

[0060] To digitize the perception of approaching the upper limit, dynamic thermal margin and pressure margin are defined and aggregated into a joint margin index; then, priority adjustment is achieved through minimum increment optimization: Where: heat margin : Upper limit of temperature level The dynamic margin can take values ​​that are positive or zero; Pressure margin : Minimum holding pressure The dynamic margin can take values ​​that are positive or zero; joint increment The optimal solution for the control increment at the current moment, the value of which is determined by the constraints; weights The cost coefficients for adjusting magnetic flux and airflow are positive; predictive mapping. The short-term prediction function based on the mechanism in step one takes real values; outer surface temperature. Casing pressure Magnetic flux target Ventilation volume Buffer capacity Time step Same as the previous definition; Therefore, implement control updates as This allows us to closely approximate the original strategic intent without sacrificing security; when heat margin Continuous convergence or pressure margin When the value drops to near the threshold, priority is given to passing through. Implement magnetic flux reduction, and then through Improve ventilation. Translate verbal priorities into weighted, solvable optimizations, enabling the controller to automatically select the less costly and safer adjustment path.

[0061] If within several steps (loop window) The minimum perturbation problem is not feasible, indicating that the current strategy number is incorrect. parameter package The current operating conditions are no longer suitable, and a rollback needs to be triggered. Infeasibility strength is measured by the minimum relaxation amount: when continued When the step size is 1 step, select the previous strategy and switch smoothly: Where: relaxation measure : Represents the minimum relaxation required to satisfy the constraint, and its value is non-negative; threshold The relaxation threshold that triggers rollback, with a non-negative value; window : The number of consecutive detection steps, with values ​​taking positive integer values; the previous policy set. : with strategy number The set of historical strategies with rollback relationships, taking values ​​from a finite set; boundary margin. The minimum margin index defined in step one can take a positive or zero value; smoothing factor. : The interpolation coefficient controls the transition between different modes of operation, and its value is [value missing]. Previous version of policy control Historical Strategy The corresponding control profile takes the value of the device's allowed domain; new control implementation The actual control after smoothing is set to the device's allowed range; the switch is implemented upon landing.

[0062] Switching and updating audit evidence simultaneously: This involves updating the switch source. ,Target Triggering factors ,window With time Aggregated into an event digest and by device key Generate a signature to serve as a backtracking basis for post-run evaluation. Use relaxation parameters and smooth interpolation to quantify when and how to roll back, avoiding jitter and facilitating clear review of responsibility boundaries.

[0063] Stitching credible evidence, restricted execution, and fallback protection into a continuous chain: using permission metrics Determine if replacement meets the standards Minimum holding pressure With the executable boundary Merge into single-point access; project the reference control with minimal disturbance. Mapping to implement control To ensure forward-looking safety; with dynamic margin Traction first lower magnetic flux Increase air volume Optimized regulation aims to achieve energy efficiency while ensuring safety; using relaxation as a metric. With window The structure is deemed infeasible and the previous version of the strategy is triggered. Smooth rollback, all switching is done via device key The generated signature is solidified as audit evidence. Ultimately, restricted execution and boundary protection are no longer additional modules, but first rules inherent in the control loop, enabling explosion-proof motors to achieve calculable, verifiable, and evolvable long-term consistency in energy-saving optimization and intrinsic safety in hazardous locations.

[0064] The fundamental goal of post-operation evaluation and strategy evolution is to transform the real trajectory generated during the constrained execution period into a quantitative deviation from the virtual baseline, and based on this, to perform constrained calibration of the heat loss and heat dissipation estimation parameters, and generate verifiable candidates for the next version of the strategy number.

[0065] Step 4: In the post-operation evaluation and strategy evolution phase, summarize the external surface temperature, shell pressure, input power, output indicators and replacement timing within the agreed time window, perform time registration and alignment with the virtual baseline, generate correction suggestions based on joint criteria and constrain the calibration of heat loss and heat dissipation parameters, reconstruct the executable boundary and constraint summary, and dynamically update the whitelist and revocation list in conjunction with vulnerability notifications to form a data and evidence link that can re-verify inputs and close the strategy evolution.

[0066] Step 401: Complete the data reliability assembly and virtual baseline alignment within the evaluation window, calculate the joint index of energy efficiency gain and safety margin change, and output the criteria for whether to trigger correction recommendations.

[0067] Point-level comparisons alone cannot reflect the coupled impact of start-stop sequences, load levels, and ventilation linkages on the heat-flow-power trajectory. Furthermore, if the data is not bound to a profile identity, there is a risk of timeline drift across devices. Therefore, policy-secure profiles must be used before proceeding with measurement. With written evidence The data source is identity converged, and then the real trajectory is projected onto the isomorphic time axis of the virtual image in step one using time registration mapping. On this basis, a joint criterion is constructed using unit output energy consumption and entropy margin measurement, so as to converge the amount of energy efficiency improvement and whether the cost is safe to a single decision quantity.

[0068] The raw data stream during operation often comes from multiple channels and different sampling rates. If it is not uniformly assembled and verified, any subsequent statistics may be based on incorrect correspondences.

[0069] First, write down the evidence. Verify the guardian parameter group With strategy number Consistent binding, and with policy security profiles The log members prove the credible starting point for the recovery assessment window.

[0070] Then, a quaternion output vector is constructed to evaluate the output vector. With virtual image output vector Through time registration mapping Minimize the alignment cost to obtain a mirror reference on a consistent timescale. The optimized form of time registration is: Where: time registration parameters : Determine the registration mapping The parameter vector takes values ​​that are differentiable in the continuous domain; Optimal registration parameters The parameter solution that minimizes the registration cost; its value is unique or selected from the equivalence class; evaluate the output vector. : From the outer surface temperature Casing pressure Input power Output indicators Composition, with values ​​taking the allowable range of each physical quantity; Mirror output vector The predicted output of the virtual image under the same event sequence and environment, with values ​​taking the allowable range of each physical quantity; weighted norm matrix. : Weight matrix used for dimensionality and importance, with values ​​being a symmetric positive definite matrix; balances registration errors across channels; registration regularization weights. : Penalty coefficient for smoothness of time mapping, with a non-negative value; Time-mapped derivative The first derivative of the registration mapping; its value should be close to 1; constrain the time velocity deviation; the starting point of the evaluation window. Evaluation window length A fixed window in the post-operation evaluation; its value is set by the operation and maintenance strategy. Based on this, the registered mirror reference and registered mirror vector are obtained. This ensures that the real and the mirrored data are comparable under the same time scale and the same event sequence. Through a two-stage process of identity binding and time registration, the uncertainty of data objects is first eliminated, and then the inconsistency of the timeline is eliminated, providing a clean comparison surface for subsequent joint indicators.

[0071] After alignment, changes in energy efficiency and safety need to be converged to a single decision value to avoid the mutual masking of energy saving and overreach. A joint index is constructed using unit output energy consumption and entropy margin, and a criterion for triggering correction is given. First, the unit output energy consumption of the actual and mirror baselines is defined: Where: actual unit output energy consumption : The ratio of energy consumed to output within the evaluation window, taken as a positive real number; mirror unit output energy consumption. The energy-output ratio of the registered image is a positive real number. Input power : Motor input power during operation, with non-negative values; output indicators The output metric defined according to the scenario (such as effective torque minus time integral or qualified parts count) is non-negative; registered mirror power. , Registration of mirror output : The mirror reference after time registration, with non-negative values; Furthermore, we define energy efficiency gain: Where: Energy efficiency gain : The improvement in energy consumption per unit output compared to the virtual baseline; the value can be positive or negative. To characterize the risk of approaching the boundary, we introduce entropy margin (temperature and pressure) and displacement time margin: Where: temperature entropy margin : By measuring the heat margin The exponential mapping measures the degree of tail-grazing, with values ​​that are non-positive or near zero; pressure entropy margin. Pressure margin Similar metrics, with values ​​that are non-positive or close to zero; Heat margin Dynamic heat margin from step three The value is non-negative; pressure margin Dynamic pressure margin from step three The value is non-negative; Temperature margin parameters Pressure margin parameters The sensitivity parameter for entropy aggregation takes a positive value; time margin. The difference between the replacement completion time and the time limit. The value can be positive or zero; the time step The prediction step size in step three is positive; it represents the short-term prediction scale.

[0072] Construct a joint score and set a criterion for exceeding the deviation limit: In the formula: joint score An indicator that combines energy efficiency gains and safety degradation in a counterbalancing manner, and is represented by a real number; Safety trade-off coefficient The penalty intensity for safety items is positive. threshold : The lower threshold for triggering correction suggestions, which takes the value of a real number; Deviation Exceedance Indication :when The value is 1 if the value is below the threshold, and 0 otherwise. When deviation exceeds the limit indication At that time, targeted correction suggestions are generated, and the sub-channels with the greatest impact are guided to the parameter calibration stage through sensitivity; when the deviation exceeds the limit indication At that time, proceed to the trace confirmation - no calibration passed.

[0073] This joint rating avoids the dilemma of energy efficiency versus safety, using entropy aggregation to capture short-term edge risks and ensure that low-probability extreme segments are not diluted by long-term averaging.

[0074] Step 402: When the deviation exceeds the limit, perform constrained calibration on the heat loss and heat dissipation estimation parameters, generate the re-verification results of the next version of the strategy number, and dynamically adjust the release whitelist and revocation list in conjunction with the vulnerability announcement to control the exposure surface and release pace.

[0075] Once a deviation is confirmed, parameters should not be manually adjusted empirically. Instead, an optimization process consistent with the mechanism and safety boundaries should be used to map the correction of the virtual image from the real trajectory to the parameter space, ensuring that the new parameters are still within the physically feasible region.

[0076] Secondly, policy revalidation should not be based solely on whether the simulation looks better; it must recalculate the executable boundaries and safety margins to create a constraint summary compatible with step one. Finally, external vulnerability notifications may change the firmware version. The risk weighting needs to combine technical deviation, parameter calibration, and external risks, and dynamically adjust the whitelist. Withdrawal List In order to control the release pace.

[0077] When transforming the true-to-mirror bias into a parameter calibration problem, direct regression with squared errors is prone to distortion at the tail bias and can disrupt the identified physical monotonicity. A Bregman divergence family is employed to minimize consistency across the temperature, pressure, and concentration channels, and a proximal canonical method is used to anchor new parameters within the neighborhood of older parameters, while also being constrained by the physically feasible region. constraint.

[0078] The calibration problem is described as follows Where: the updated parameter vector The parameters obtained from this calibration solution are subject to the following values: limit; Parameter vector Includes thermonuclear amplitude Thermal time constant Heat source coefficient Heat dissipation coefficient Ventilation nonlinear index Effective volume Leakage coefficient Leakage nonlinear index The physical reasonable domain that takes a value that is positive or greater than or equal to 1; feasible region : A set of parameters consisting of physical constraints and prior boundaries (e.g. ), which takes the value of a subset of the parameter space; Bregman divergence : From convex potential function The induced divergence, with non-negative values, uses a metric that better penalizes tail errors for different channels (e.g., ); external surface temperature Casing pressure Combustible volume fraction : The true trajectory state, with values ​​taken from their respective physical domains; mirror prediction , , :parameter The virtual image output is set to its respective physical domain; near-end regularization. : with convexity The distance between the old and new parameters is measured, and the value is non-negative; the old parameter The parameter vector that passed the last validation; its value is... Internal; Regular weights : Proximal canonical intensity, with a non-negative value; To minimize interference with the control loop, calibration employs near-end iteration using natural gradients: Where: loss function The sum of the integral term and the regularization term in the above equation takes the value of a non-negative real number; the natural gradient metric matrix. The Riemannian metric approximated by the sensitivity matrix takes the value of symmetric positive definite; step size : The step size for iterative updates, taking a positive value to control the convergence speed; inner product Weighted norm Standard inner product and - Weighted norm, taking values ​​of real numbers; When parameter Once obtained, immediately rebuild the virtual image under the new parameters and recalculate the key quantities from step one: Where: Safe temperature difference after update : In parameters Temperature margin, which can be positive or zero; replacement completion time after update. Based on the updated displacement dose function The calculation completion time is non-negative. Executable boundary approximation after update The polyhedral boundary reconstructed by perturbation scanning is taken as a half-space family; the simulation time domain length is... : Mirror simulation time domain length, positive value; permutation dose function :exist The next replacement dose will be a real number. By mapping the deviation to the parameter space and maintaining physical constraints, we can avoid making the calibration look good but using it dangerously. We can also immediately transfer the calibration results back to the criterion system of step one through recalculation and boundary reconstruction to ensure consistency across steps.

[0079] Parameter calibration does not mean an immediate large-scale release; it is still necessary to comprehensively consider external vulnerability notifications and historical robustness to manage the distribution of policy numbers. Define firmware version-specific requirements. Equipment identification The risk intensity index is used to adjust the whitelist. Withdrawal List Simultaneously, a release pacing factor is calculated to control the scrolling speed. First, the strategy improvement score and risk intensity are defined: Where: Improved joint score Use updated metrics The calculated overall score is a real number; risk intensity Collection of Vulnerability Announcements The aggregated risk of abnormal operation signals is non-negative; Vulnerability notification set. Affects firmware version The set of external notifications, whose values ​​are a finite set; event weights. Regarding the announcement event The severity weight, with a non-negative value; the probability of being exploited. Regarding the event The probability of utilization is estimated, taking a value of ; Anomaly Indication : A binary or fractional indicator based on runtime anomaly detection, with non-negative values; anomaly weight : Weights of outliers, with non-negative values; updated energy efficiency gain Entropy margin Time margin : In parameters The recalculated indicators will have the same values ​​as before; Based on the above quantities, define the update rules and release cadence factors for the whitelist and revocation list: In the formula: the updated whitelist : The set of policies allowed to enter the publishing window, whose value is a subset of the entire set of policies; the list of policies to be revoked after update. : The set of policies that need to be immediately blocked or revoked, where each value is a subset of the entire set of policies; energy efficiency threshold The minimum revenue requirement for the whitelist, which is a real number; Risk threshold Cancellation threshold : These are the risk thresholds used for whitelisting and revocation, respectively, and their values ​​are non-negative; Temperature difference buffer : Safety temperature difference baseline, with a non-negative value; boundary margin The minimum margin of historical strategies, which can be positive or zero; release rhythm factor. : A coefficient that determines the speed of batch releases, with a value of Baseline tempo upper limit Span parameters Risk inhibition coefficient : A parameter for adjusting the release schedule; the value should be positive. When the updated strategy number and When the number is large enough, proceed to the next round of limited-scale grayscale release; if If so, the platform side immediately updates the revocation list and communicates it to the edge via the log root to ensure consistency across the entire chain.

[0080] The release schedule is constrained by the intensity of risk, and the technical improvements after parameter calibration are placed in a governance framework that is scalable, reversible, and rhythmic, ensuring that optimization and risk management go hand in hand.

[0081] Step 403: Execute a canary release orchestration based on risk-reward synergy, and aggregate the operational evidence into archive-level updates to achieve a closed-loop drive for redistribution and reverification; Before proceeding to the release phase, the release pacing factor obtained in step 402 needs to be... Safety margin information is disseminated at the device level, ensuring that the dissemination follows the overall rhythm while respecting local operating condition differences.

[0082] Therefore, the first step is to design the device pool. Constructing the distribution probability device distribution probability It comprehensively considers equipment risk weights, operating condition similarity, and safety buffer scaling to avoid pushing the new strategy to edge equipment where the safety temperature difference and pressure margin are already approaching the threshold. Where: Equipment allocation probability :Strategy Equipment identification The grayscale delivery probability is set to a value. And for Normalization; minimum temperature margin :equipment The minimum pressure margin is determined by the heat margin of the most recent observation window, and its value is non-negative. :equipment The pressure margin lower bound is non-negative; temperature difference buffer. Pressure buffer : A conservative buffer set before deployment, with a non-negative value; Release pacing factor The rhythm upper limit coefficient output in step 402 has a value of [value missing]. Equipment risk weight Risk coefficients based on historical equipment anomalies and environmental levels are non-negative. Operating condition similarity :equipment The similarity score with the simulation condition in step one is set to a value of [value]. It can be derived from the Euclidean-Markovian hybrid metric of the mirror-site feature vectors; the product of temperature scaling and pressure scaling: the probability of jointly suppressing low-margin devices; scale parameters. : Assign softening temperature, with a positive value; equipment pool The set of devices that can currently participate in grayscale testing, with values ​​belonging to a finite set; Based on device allocation probability After generating the first batch of grayscale groups, the runtime continuously calculates the joint score for each device. Relaxation measurement with equipment side and with a stop instruction Adaptive gate for batch diffusion: When the proportion of low scores exceeds the threshold, the diffusion process is immediately frozen and enters a correction and review phase; when high scores appear stably and the relaxation amount remains below the threshold for an extended period, the process is... The remaining weights are increased to release the next batch of equipment.

[0083] By employing a three-tiered rule of rhythm, probability, and gate, the release process maintains respect for safety boundaries at both the statistical and individual levels, avoiding unbalanced diffusion caused by a single indicator. Global rhythm and local safety are coupled multiplicatively into the same allocation formula, ensuring that each diffusion aligns with the overall strategy's benefits without sacrificing the safety margin of the most vulnerable individuals.

[0084] Gray-scale releases only have lasting value if the evidence can be faithfully preserved and reused. This involves mapping device-side scores, relaxation values, and anomaly indicators to credibility gains. This serves as a unified threshold for whether to upgrade to a stable version and whether to re-upload the archive; at the same time, a merge operation is performed at the archive level to bind the new evidence and the existing signature-time stamp-log root to the same non-repudiable structure.

[0085] Where: Confidential gain : A credibility metric after aggregating operational evidence, with a non-negative value; joint score on the device side. :equipment Top Strategy The joint score is a real number; the equipment-side relaxation metric. The minimum relaxation required to satisfy the constraint, with a non-negative value; relaxation threshold. : Infeasibility trigger threshold, with a non-negative value; anomaly indicator :equipment The abnormal event intensity or binary indicator, with a non-negative value; weight The aggregate weights of the three types of evidence are non-negative; the Sigmoid function is used. Mapping the original quantity to Compression function; suppresses extreme values. Device pool Same as above; aggregation domain.

[0086] when And the updated safe temperature difference from the batch Replacement time after update Still satisfied At that time, perform file-level merging: In the formula: file upgrade The policy security profile after merging the evidence is a structured object. Merge Operator : The original file Integrity check value Time stamp , log root and new evidence Deterministic mapping for consistent merging; Integrity check value Time stamp , log root The element defined in step two takes the value of a fixed-length summary; Collection of evidence :Depend on and the set consisting of the corresponding timelines; updated constraint summary : The minimum sufficient set used for revalidation in step one, with values ​​being structured tuples; Updated safety temperature difference Replacement time after update Updated Executable Boundaries Updated compliance instructions Updated firmware version All of these are from the re-verification process in step 402, ensuring that the redistribution remains within hard constraints.

[0087] like If the policy level is frozen in the whitelist, the relevant devices and versions are added to the review queue. The evidence is still written to the archive but marked as a restricted sample, for reuse in the parameter near-end calibration in step 402. Thus, the evidence is neither wasted nor misused in the full release. Using trusted gain as a unified metric for upgrades and refeedback, the operational facts, release governance, and archive anchor points are closed onto the same evidence chain, ensuring traceability and avoiding conflicting accounts.

[0088] Through this step, the release and evolution process is upgraded from experience-driven to evidence-driven: In global speed regulation, In local allocation, the two are coupled with the scaling of thermal-pressure dual margin to ensure that the load-bearing capacity and boundary safety of each batch of equipment are matched in real time; The device-side score, relaxation metric, and anomaly indication are uniformly converted into a credibility threshold, and the criteria for whether to upgrade to a stable version and whether to re-install as an archive anchor are combined into the same judgment; merge operators. Then combine the new evidence with Binding, generation and This provides the latest and verifiable input for the constrained virtual image verification in the next round of Step One. When entering subsequent loops, Step Two can then... A trusted release is then performed again. Step three involves continued execution and rollback protection based on the device's real-time margin; this process is repeated until the temperature level limit is reached. Minimum holding pressure Maximum replacement time Under these three hard constraints, the strategy iteration proceeds with small-step safety diffusion and converges based on factual evidence, ultimately achieving intelligent energy-saving adaptive optimization of explosion-proof motors in hazardous locations that is calculable, verifiable, and evolvable.

[0089] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0090] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0091] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0092] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0093] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for intelligent energy-saving adaptive optimization control of explosion-proof motors, characterized in that: include, Build a virtual image and set the upper limit of temperature level, minimum holding pressure and replacement completion time as hard constraints; import strategy number, parameter package and firmware version for simulation, generate safe temperature difference, replacement compliance judgment and executable boundary, and output candidate list and constraint summary; A policy security profile is generated for the candidate list, including source signature, integrity check value, firmware version and device compatibility; the signature and timestamp are verified, and the cancellation list is used to block the failure; Devices that pass verification and whose device identifiers match will be put into deployment, and the three constraints mentioned above will be registered as guardian parameters. Enable restricted execution, write the guardian parameters to the read-only area and bind them to the file; control the executable boundary projection according to the statement; disable startup if the replacement fails to meet the standard or the pressure is lower than the minimum holding pressure; reduce magnetic flux and increase ventilation when the temperature approaches the upper limit; if not feasible, revert to the previous version; The system summarizes temperature, pressure, input power, output, and displacement timing within a specified window, aligns it with the virtual mirror baseline, and calculates the metrics. When deviations exceed limits, it generates correction suggestions, updates parameters, and reconstructs the executable boundary and constraint summary. It also adjusts the whitelist and revocation list based on vulnerability notifications.

2. The intelligent energy-saving adaptive optimization control method for explosion-proof motors according to claim 1, characterized in that: The virtual image adopts a three-domain coupled model of device, environment and safety clauses. The state includes external surface temperature, shell pressure and combustible volume fraction. The control input includes ventilation volume and magnetic flux target. The three hard constraints are embedded in the form of obstacles. The executable boundary is fixed in the constraint summary as polyhedral parameters. The boundary parameters are generated by perturbation scanning and operating condition layering. The parameters are stored in a one-to-one association with the index of the parameter package and the policy number.

3. The intelligent energy-saving adaptive optimization control method for explosion-proof motors according to claim 2, characterized in that: The replacement compliance determination is constructed by the evolution of replacement dose and concentration, and the safe temperature difference and pressure margin are calculated within the exercise time window. The candidate list is generated and the corresponding constraint summary is recorded according to the conditions that the replacement compliance determination is true, the safe temperature difference is not lower than the threshold and the executable boundary is not empty. The exercise sequence includes the actual start-up and shutdown sequence and ventilation linkage mapping, and the entry number is saved in the mirror database.

4. The intelligent energy-saving adaptive optimization control method for explosion-proof motors according to claim 3, characterized in that: The policy security profile uses structured messages to sequentially bind the constraint summary, the policy number, the firmware version, and the device identifier, and introduces domain tags to generate integrity verification values; The system combines time stamping, membership verification, and log root writing. The revocation list adopts a verifiable set structure for subsequent verification calls, and generates signatures through forward secure key chain evolution and archives them on the platform side.

5. The intelligent energy-saving adaptive optimization control method for explosion-proof motors according to claim 4, characterized in that: A joint admission criterion is set in the platform-to-controller link, including signature verification result, log membership, latency window and the revocation list status; The device identifier consistency and rollback conditions are further filtered to generate the set to be deployed. The device side uses a key to form write evidence for the guardian parameters, the policy number and the firmware version, and records the reason code and time stamp and sends it back to the platform.

6. The intelligent energy-saving adaptive optimization control method for explosion-proof motors according to claim 5, characterized in that: Upon going online, the written evidence is read, the guardian parameters are fixed in the read-only area, and a permission index is constructed that includes the replacement compliance determination, the shell pressure is not lower than the minimum holding pressure, and the initial configuration falls within the executable boundary; when the permission is granted, the reference control is safely projected to generate the implementation control, otherwise the loading is stopped and the rejection classification and rejection source are output.

7. The intelligent energy-saving adaptive optimization control method for explosion-proof motors according to claim 6, characterized in that: During operation, the priority order of first reducing the magnetic flux target and then increasing the ventilation volume is adopted, and the implementation control is continuously updated by combining short field-of-view sequence projection and control rate limiting. When it is not feasible within a continuous window and the relaxation metric exceeds the threshold, the previous version of the strategy is selected and the switch is smoothly performed by the interpolation factor. At the same time, a switch event summary is generated, signed and filed, and the switch count and the most recent effective batch number are recorded in the controller's read-only area.

8. The intelligent energy-saving adaptive optimization control method for explosion-proof motors according to claim 7, characterized in that: Within the agreed evaluation window, the outer surface temperature, shell pressure, input power, output and replacement timing are reliably assembled and aligned with the virtual mirror baseline after time registration. A joint criterion is constructed for unit output energy consumption, temperature, pressure, and displacement time. When the deviation exceeds the threshold, the aforementioned correction suggestion is generated and the calibration process is initiated. The evaluation data adopts a unified sampling rate and time-scaled calibration strategy and retains the registration parameter set.

9. The intelligent energy-saving adaptive optimization control method for explosion-proof motors according to claim 8, characterized in that: The parameters such as heat loss, heat dissipation, effective volume and leakage are calibrated in the physically feasible region using Bregman divergence and near-end regularization, the executable boundary is reconstructed and the constraint summary is updated, and the updated strategy number is output. The whitelist and the revocation list are adjusted synchronously based on the risk intensity and release rhythm factor, and the parameter change history and calibration iteration number are retained for subsequent retrieval.

10. The intelligent energy-saving adaptive optimization control method for explosion-proof motors according to claim 9, characterized in that: The grayscale release orchestration is based on the release rhythm factor, equipment risk weight, operating condition similarity, and minimum margin of temperature and pressure to calculate the equipment allocation probability; Within a batch, the joint score and relaxation metric of the device side are continuously statistically analyzed, and the data is frozen or incrementally released according to the stop indication. After aggregating the running evidence, the archive is merged and an updated constraint summary is generated as the sole entry point for the next round of virtual image verification, and the batch topology is archived on the platform.

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