Lamp language system of power station secondary system

Abstract

The invention relates to the technical field of lamp language monitoring management, in particular to a lamp language system of a power station secondary system, which comprises a data acquisition module, a state analysis module, a lamp language mapping and generating module and a lamp language presentation device, the data acquisition module acquires data of protection, measurement and control, communication and power subsystems in parallel, and feature vectors are formed through preprocessing and feature fusion; the state analysis module divides system states into emergency, abnormity, attention and normal through a fuzzy logic model, identifies abnormity in combination with a diagnosis rule base and generates an abnormal event code with a time scale; the lamp language mapping and generating module maps the state level into a basic lamp language mode, maps the abnormal code into an enhanced lamp language element, and performs space-time superposition to generate a composite control instruction; the lamp language presentation device drives the RGB-LED array and the light beam deflection mechanism, and dynamic light signals with spatial directivity are presented on the simulation screen. According to the invention, monitoring comprehensiveness and state identification accuracy are improved, operation and maintenance response is accelerated, and reliable operation of the secondary system is guaranteed.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of lamp language monitoring management, in particular to a lamp language system of a secondary system of a power station. BACKGROUND

[0002] The secondary system of the power station is a core support link for ensuring the safe and stable operation of the primary system of the power station, which covers four key subsystems of protection, measurement and control, communication and power supply. The running state of the system is directly related to the operation and maintenance efficiency and safety performance of the whole power station. Therefore, real-time monitoring, accurate analysis and intuitive presentation of the running state of the secondary system become an important demand for the operation and maintenance work of the power station.

[0003] The current industry monitoring scheme for the secondary system of the power station has many technical defects. In the data acquisition layer, the existing monitoring system mostly adopts the mode of independent acquisition of a single subsystem, which cannot realize the parallel and synchronous acquisition of the running state data of the four subsystems of protection, measurement and control, communication and power supply, resulting in lack of consistency in time dimension of data. At the same time, for the raw data such as protection device action sequence signal, measurement and control device analog quantity out-of-limit signal, communication network time delay jitter signal and power supply system ripple abnormal signal collected, there is lack of effective pretreatment means, and no action number statistics and time sequence alignment, signal effectiveness verification, time domain filtering, frequency domain analysis and other operations are performed. The raw data is easily disturbed by environmental noise, and the data accuracy and effectiveness are insufficient, which is difficult to form an effective data basis that can fully represent the overall running state of the secondary system.

[0004] In the state analysis layer, the state evaluation method of the existing system mostly relies on a single characteristic index for judgment, without introducing multi-source information fusion technology and fuzzy logic analysis model, which cannot perform four-level accurate classification evaluation of the system running state, such as "emergency, abnormal, attention, normal", and the state judgment is easy to be one-sided or misjudged. In addition, abnormal pattern recognition mostly relies on the artificial experience of operation and maintenance personnel, lacks a standardized diagnostic rule base constructed based on historical fault data of the secondary system of the power station, and is difficult to automatically extract abnormal characteristic indexes and match with rule conditions, resulting in difficulty in abnormal positioning, inability to quickly determine the fault subsystem and specific fault type, and inability to record the accurate time information of abnormal occurrence, which hinders subsequent fault tracing and analysis.

[0005] In the state presentation layer, the existing system transmits state information through a text report, a numerical display interface or a simple indicator light, the information transmission form is single and poor in intuitiveness. In the scene where multiple systems in the main control room are running simultaneously and various monitoring information is dense, the operation and maintenance personnel need to spend a lot of time screening key state information from the complex text or numbers, and it is difficult to quickly capture abnormal changes in the system; some presentation methods do not design spatial directionality function, and cannot accurately point to the physical area corresponding to the fault subsystem through visual signals, which prolongs the fault troubleshooting time; at the same time, the existing display device is prone to display information blurring and low recognition in harsh operating environments such as strong light irradiation or electromagnetic interference, which further affects the effective transmission of state information, therefore, the lamp language system of the secondary system of the power station is proposed to solve the above problems. SUMMARY

[0006] The purpose of the present application is to provide a lamp language system of a secondary system of a power station to solve the problems raised in the background art.

[0007] To achieve the above purpose, the present application provides the following technical solutions: The lamp language system of the secondary system of the power station comprises: A data acquisition module is configured to acquire real-time operation state data of four subsystems of the secondary system of the power station, including a protection subsystem, a measurement and control subsystem, a communication network and a power supply system, wherein the operation state data includes an action sequence signal of the protection device, an analog quantity out-of-limit signal of the measurement and control device, a time delay jitter signal of the communication network and a ripple abnormal signal of the power supply system; A state analysis module is in communication connection with the data acquisition module, configured to perform multi-source information fusion on the operation state data to establish a state evaluation model based on fuzzy logic, and identify abnormal patterns in the operation state data based on a pre-set diagnostic rule base, and output a comprehensive system state level and at least one abnormal event code with time stamp information; wherein the system state level is divided into four levels of emergency, abnormality, attention and normality, and the abnormal event code contains fault location identification and fault type identification; A lamp language mapping and generation module is in communication connection with the state analysis module, and internally pre-stores a lamp language coding rule base; configured to receive the system state level and the abnormal event code, query the lamp language coding rule base to map the system state level into a basic lamp language mode containing a base color and a basic flicker frequency, and map the abnormal event code into enhanced lamp language elements containing a color halo parameter, an additional flicker sequence mode and a light beam scanning direction, and then superimpose the basic lamp language mode and the enhanced lamp language elements in time and space to generate a composite lamp language control instruction; The lamp language presentation device is connected with the lamp language mapping and generating module, and is configured to receive the composite lamp language control instruction, and drive a plurality of light sources including an RGB-LED array and a light beam deflection mechanism, to present a dynamic light signal with spatial directivity on a large analog screen in the main control room of the power plant by controlling each light source through the composite lamp language control instruction; wherein the spatial directivity is achieved by controlling the scanning direction of the light beam through the light beam deflection mechanism.

[0008] As a preferred solution, the data acquisition module is configured to acquire, in real time, the operation state data of the four subsystems of the secondary system of the power plant, including: the action sequence signals of the protection devices of the protection subsystem, the analog quantity overrun signals of the measurement and control subsystem, the network time delay jitter signals of the communication subsystem, and the DC power supply ripple abnormal signals of the power supply subsystem are acquired in parallel; the acquired protection device action sequence signals are subjected to action number statistics and time sequence alignment processing, the analog quantity overrun signals are subjected to signal validity verification and overrun amplitude classification processing, the network time delay jitter signals are subjected to time domain filtering and jitter intensity calculation processing, and the DC power supply ripple abnormal signals are subjected to frequency domain analysis and ripple coefficient extraction processing; the protection action frequency features and action logic relationship features are extracted based on the preprocessed action sequence signals, the overrun duration features and overrun trend features are extracted based on the preprocessed analog quantity overrun signals, the communication quality degradation features are extracted based on the preprocessed network time delay jitter signals, and the power supply stability features are extracted based on the preprocessed DC power supply ripple abnormal signals; the extracted protection action frequency features, action logic relationship features, overrun duration features, overrun trend features, communication quality degradation features, and power supply stability features are subjected to feature-level fusion to form a feature vector representing the overall operation state of the secondary system of the power plant; the feature vector is delivered to the state analysis module as input data of the fuzzy logic-based state evaluation model.

[0009] As a preferred solution, the state analysis module is configured to perform multi-source information fusion on the operation state data to establish a fuzzy logic-based state evaluation model, including: receiving the feature vector delivered by the data acquisition module; standardizing the feature vector for preprocessing to eliminate differences in dimensions and numerical ranges of different features, to generate a standardized feature vector; inputting the standardized feature vector into a predefined fuzzy logic state evaluation model, wherein the fuzzy logic state evaluation model includes fuzzy sets and membership functions defined for each feature, for converting each feature value into a membership degree of the corresponding fuzzy set; The fuzzy membership degrees are calculated by fuzzy reasoning based on the preset fuzzy rule base, and the fuzzy membership degrees corresponding to the four state levels of emergency, abnormality, attention, and normality of the power station secondary system are calculated. The fuzzy membership degrees are de-fuzzified, and the fuzzy output is converted into an accurate preliminary system state level by the gravity center method or the maximum membership degree method. The preliminary system state level is output, and it is used as the basis for abnormal pattern recognition and comprehensive state decision.

[0010] As a preferred solution, the state analysis module identifies abnormal patterns in the operating state data based on a preset diagnostic rule base, and outputs a comprehensive system state level and at least one abnormal event code with timestamp information, including: Receiving the preliminary system state level; Extracting abnormal feature indicators corresponding to the preset diagnostic rule base from the feature vector, including protection action frequency abnormality indicators, analog quantity out-of-limit duration abnormality indicators, network time delay jitter intensity abnormality indicators, and power source ripple coefficient abnormality indicators; Matching the abnormal feature indicators with the rule conditions in the diagnostic rule base one by one, wherein the diagnostic rule base contains rules predefined based on the historical fault data of the power station secondary system, and each rule is associated with an abnormal feature indicator threshold and a corresponding abnormal pattern type; When the abnormal feature indicator exceeds the threshold defined in the rule condition, the corresponding abnormal pattern is triggered, and the exact timestamp of the abnormal occurrence is recorded; Generating an abnormal event code according to the triggered abnormal pattern, wherein the fault location identification is automatically assigned based on the subsystem to which the abnormal feature indicator belongs, and the fault type identification is automatically mapped based on the triggered abnormal pattern type; Sorting all triggered abnormal patterns according to the preset severity grading rules, and combining the preliminary system state level for fusion calculation, and determining the final comprehensive system state level through weighted evaluation; Outputting the comprehensive system state level and at least one abnormal event code with timestamp information to the light language mapping and generation module.

[0011] As a preferred solution, the light language mapping and generation module is used to receive the system state level and the abnormal event code, and generate a composite light language control instruction, including: Receiving the system state level and at least one abnormal event code with timestamp information from the state analysis module, and initializing a light language control data structure; Querying the pre-stored light language coding rule base, mapping the corresponding base color and basic flicker frequency according to the system state level, and setting the base color and basic flicker frequency in the light language control data structure to form a basic light language pattern; Based on the processed lamp language control data structure, the lamp language coding rule library is queried, the corresponding color halo parameter, additional flashing sequence mode and light beam scanning direction are mapped according to the fault position identifier and fault type identifier in the abnormal event code, and the enhanced lamp language elements are added to the lamp language control data structure; The basic lamp language mode and the enhanced lamp language elements in the processed lamp language control data structure are integrated in time and space, wherein the time integration includes synchronously arranging the basic flashing frequency and the additional flashing sequence mode, and the space integration includes fusing the base color and the color halo parameter and determining the spatial directivity through the light beam scanning direction, so as to generate a composite lamp language control instruction.

[0012] As a preferred scheme, the lamp language presentation device performs the following processing flow to realize the generation and presentation of the dynamic light signal: The composite lamp language control instruction from the lamp language mapping and generation module is received, and the instruction is parsed to extract the basic lamp language mode parameters and the enhanced lamp language element parameters contained therein; The basic lamp language mode parameters parsed are converted into driving signals of the RGB-LED array, wherein the base color parameter corresponds to the proportioning value of the RGB three primary colors, and the basic flashing frequency parameter corresponds to the periodic on-off timing of the LED light source; According to the color halo parameter in the enhanced lamp language element, an additional color effect is superimposed on the base color of the basic lamp language mode to generate a halo control signal with color gradient levels; The additional flashing sequence mode and the basic flashing frequency are time-synchronized to form an integrated flashing control signal containing a composite flashing rule; The light beam scanning direction parameter is converted into a control instruction of a light beam deflection mechanism to determine the dynamic scanning path of the light beam emitted by the RGB-LED array on the large simulation screen; The RGB-LED array and the light beam deflection mechanism are synchronously driven, so that the RGB-LED array emits a light beam with specific color, flashing rule and halo effect according to the integrated flashing control signal and the halo control signal, and the light beam deflection mechanism guides the light beam to deflect along the specified scanning path according to the control instruction; Through the cooperative work of multiple groups of light sources, a dynamic light signal with spatial directivity is formed on the large simulation screen, wherein the spatial directivity is represented by the scanning track and the stopping position of the light beam on the simulation screen.

[0013] As can be seen from the above technical solutions provided by the present application, the lamp language system of the secondary system of the power plant provided by the present application has the beneficial effects that: The data acquisition module can acquire the operation state data of four subsystems of the power station secondary system in parallel, eliminate data interference through preprocessing operations such as action frequency statistical time alignment signal effectiveness verification, time domain filtering and frequency domain analysis, and then form a feature vector representing the overall operation state of the system through feature level fusion, ensuring that the data delivered to the subsequent module covers the key subsystems and is accurate and reliable, and providing a solid data foundation for system state evaluation; The state analysis module constructs a state evaluation model based on fuzzy logic, divides the system state into four levels of emergency, exception, attention and normal, and generates a preliminary state level through standardized preprocessing and fuzzy inference; meanwhile, it extracts abnormal feature indicators from a preconfigured diagnostic rule library, matches them with rule conditions to trigger abnormal patterns, and generates an abnormal event code containing fault location identification, fault type identification and time stamp, which can accurately judge the overall operation state of the system and accurately identify the subsystem and specific type of the abnormality, providing clear guidance for fault location; The light language mapping and generation module maps the system state level to a basic light language mode containing primary colors and basic flicker frequency, maps the abnormal event code to an enhanced light language element containing color halo parameters, additional flicker sequence mode and beam scanning direction, and generates a composite light language control instruction through space-time superposition, so that the light language can simultaneously convey the overall system state and abnormal detail information, breaking through the information limitation of single light language mode and meeting the personnel's demand for obtaining different level state information; The light language presentation device realizes color fusion of primary colors and halos, time sequence synthesis of basic and additional flickers through an RGB-LED array, controls the beam scanning direction through a beam deflection mechanism, and forms a dynamic light signal with spatial directionality on a large simulation screen; this light signal is intuitive and easy to understand, and personnel can quickly identify the system state and abnormalities through color flicker rules and scanning trajectories, and the high brightness and high contrast characteristics of RGB-LED ensure that the information is still clear and readable in harsh environments such as strong light or electromagnetic interference in the main control room; The system runs automatically in the whole process from data acquisition to light language generation and presentation, reducing the need for manual intervention, and personnel can quickly grasp the system state and abnormal conditions through light language without checking subsystem data one by one, greatly shortening the state recognition and fault location time; meanwhile, the time stamp information and fault identification of the abnormal event code facilitate the tracing of abnormal processes by operation and maintenance personnel, reducing the workload of fault troubleshooting and reducing operation and maintenance time and labor costs; Supports long-term reliable operation of the power station secondary system; the system can monitor and record the operation state and abnormal events of the secondary system in real time, and the historical data formed can assist operation and maintenance personnel in summarizing fault rules, such as the high incidence period of common abnormal types of specific subsystems, thereby optimizing operation and maintenance plans, conducting targeted hidden trouble troubleshooting in advance, reducing the probability of faults, and improving the long-term operation reliability and stability of the power station secondary system. BRIEF DESCRIPTION OF DRAWINGS

[0014] Figure 1 This is a schematic diagram of the overall structure of the lighting system of the secondary system of the power plant according to the present invention. Detailed Implementation

[0015] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0016] To better understand the above technical solutions, the following will provide a detailed explanation of the technical solutions in conjunction with the accompanying drawings and specific embodiments.

[0017] like Figure 1 As shown, this embodiment of the invention provides a signaling system for a power plant's secondary system, comprising: Data acquisition module: used to collect real-time operating status data of four subsystems in the secondary system of the power plant: protection, measurement and control, communication and power supply. The operating status data includes the action sequence signals of protection devices, the analog quantity over-limit signals of measurement and control devices, the time delay jitter signals of communication networks and the ripple abnormal signals of the power supply system. Status Analysis Module: Communicates with the data acquisition module to perform multi-source information fusion on the operating status data to establish a fuzzy logic-based status assessment model. Based on a pre-set diagnostic rule base, it identifies abnormal patterns in the operating status data and outputs a comprehensive system status level and at least one abnormal event code with time stamp information. The system status level is divided into four levels: emergency, abnormal, attention, and normal. The abnormal event code includes a fault location identifier and a fault type identifier. The light language mapping and generation module communicates with the status analysis module and has a pre-stored light language encoding rule library. It is used to receive system status levels and abnormal event codes, query the light language encoding rule library to map the system status level to a basic light language mode containing primary colors and basic flashing frequencies, and to map abnormal event codes to enhanced light language elements containing color halo parameters, additional flashing sequence modes and beam scanning directions. Then, it spatiotemporally superimposes the basic light language mode and enhanced light language elements to generate composite light language control commands. Light signal presentation device: connected to the light signal mapping and generation module, used to receive composite light signal control commands and drive multiple light sources including RGB-LED arrays and beam deflection mechanisms. On the large simulation screen in the main control room of the power plant, the composite light signal control commands control each light source to present a dynamic light signal with spatial directionality; wherein, spatial directionality is achieved by beam deflection mechanism to control the beam scanning direction.

[0018] In this embodiment, the data acquisition module is the "data cornerstone" of the power station secondary system lamp language system. It collects, preprocesses, extracts and fuses the running state data of the four core subsystems of protection, measurement and control, communication and power supply in the secondary system in real time, provides accurate and comprehensive input data for the subsequent state analysis module, and ensures that the entire lamp language system can generate effective lamp language based on the real running state; The data acquisition module is mainly responsible for real-time acquisition of the running state data of the four subsystems of protection, measurement and control, communication and power supply in the secondary system of the power station. These data specifically include the action sequence signals of the protection device, the analog quantity overrun signals of the measurement and control device, the time delay jitter signals of the communication network and the ripple abnormal signals of the power supply system. The module will preprocess the collected raw data, remove interference and extract key features, then fuse the features of each subsystem to form a feature vector that can represent the overall running state of the secondary system. Finally, the feature vector is delivered to the state analysis module as input data for the subsequent fuzzy logic state evaluation model, providing data support for system state level judgment and abnormal mode recognition, including: Parallel acquisition unit: Multi-channel synchronous acquisition technology is used to simultaneously acquire the running state data of the four subsystems. Specifically, it includes collecting the protection device action sequence signals of the protection subsystem, the analog quantity overrun signals of the measurement and control subsystem, the network time delay jitter signals of the communication subsystem and the DC power supply ripple abnormal signals of the power supply subsystem. Through parallel acquisition design, the data of the four subsystems is kept synchronized in the time dimension, avoiding deviations in subsequent analysis caused by differences in acquisition timing, and ensuring the time consistency and integrity of the data. Parallel acquisition technology is based on a multi-channel synchronous acquisition architecture, which configures independent signal acquisition channels for the four subsystems of protection, measurement and control, communication and power supply. Each channel uses the same sampling clock to ensure that the running state signals of different subsystems are collected at the same time, eliminating data time deviations caused by different sampling timings. This technology can simultaneously acquire multi-source data, ensuring the time synchronization of the data, laying a foundation for subsequent multi-subsystem collaborative analysis, and avoiding the low efficiency and timing confusion problems caused by single-channel serial acquisition. Data preprocessing unit: Differentiated preprocessing operations are performed on different types of signals obtained by the parallel acquisition unit; the action sequence signal of the protection device is subjected to action frequency counting and time sequence alignment processing to ensure that the time sequence of the action signal is accurate and quantifiable; the analog quantity overrun signal is subjected to signal validity verification and overrun amplitude grading processing to eliminate invalid signals and distinguish the severity of overrun; the network time delay jitter signal is subjected to time domain filtering and jitter intensity calculation processing to filter high-frequency noise and quantify the jitter degree; the DC power supply ripple abnormal signal is subjected to frequency domain analysis and ripple coefficient extraction processing to determine the frequency characteristics and intensity index of the ripple; The core goal of the preprocessing operation is to eliminate noise, interference and invalid information in the original data, convert the data into a standard format that meets the requirements of subsequent feature extraction, and improve the data quality; The data preprocessing technology adopts differentiated processing methods for different types of signals; for the action sequence signal of the protection device, the time stamp deviation of the signal is corrected through a time sequence alignment algorithm, and the number of actions per unit time is counted to realize the quantification and standardization of the signal; for the analog quantity overrun signal, abnormal values caused by sensor failure or interference are eliminated through an effectiveness verification algorithm, and the overrun amplitude is graded according to a pre-set threshold to determine the severity of the overrun; for the network time delay jitter signal, a time domain filtering algorithm (such as a moving average filter) is used to filter high-frequency noise, and the standard deviation of the time delay is calculated as the jitter intensity index; for the DC power supply ripple abnormal signal, the frequency components of the ripple are decomposed through frequency domain analysis methods such as Fourier transform, and the ripple intensity is quantified by extracting the ripple coefficient; this technology effectively improves the data quality through targeted processing and provides a reliable foundation for feature extraction; Feature extraction unit: Based on the preprocessed signals of various types, key features reflecting the running state of the corresponding subsystem are extracted; from the preprocessed action sequence signal of the protection device, protection action frequency features and action logic relationship features are extracted, the former representing the action frequency of the protection device and the latter reflecting the correlation between actions; from the preprocessed analog quantity overrun signal, overrun duration features and overrun trend features are extracted, the former representing the duration of the overrun state and the latter showing the change direction and rate of the overrun amplitude; from the preprocessed network time delay jitter signal, communication quality degradation features are extracted to quantify the transmission stability of the communication network; from the preprocessed DC power supply ripple abnormal signal, power supply stability features are extracted to reflect the power supply stability of the power supply system; The extracted features need to be representative and accurately map the running state of the subsystem to provide detailed basis for subsequent overall system state evaluation; The feature extraction technology extracts key information from the preprocessed signals based on the correlation law of the signals and the operating state of the subsystem. For the protection device action sequence signal, the action frequency directly reflects the activity level of the protection system, and the action logic relationship reflects the cooperative working state of the protection device. The combination of the two can map the operating stability of the protection subsystem. For the analog quantity overrun signal, the longer the overrun duration and the steeper the overrun trend, the more serious the abnormality of the measurement and control subsystem. For the network time delay jitter signal, the communication quality degradation characteristics are reflected by the deviation of the time delay jitter intensity from the preset normal range, directly reflecting the transmission quality of the communication subsystem. For the DC power supply ripple abnormal signal, the power supply stability characteristics are characterized by the ripple coefficient. The larger the ripple coefficient, the worse the power supply stability. This technology converts the original data into feature indicators that can reflect the state of the subsystem by mining key information from the signals. Feature fusion unit: All features output by the feature extraction unit are collected, including protection action frequency features, action logic relationship features, overrun duration features, overrun trend features, communication quality degradation features, and power supply stability features. The feature-level fusion method is used to integrate the above scattered subsystem features into a unified feature vector. This feature vector can comprehensively reflect the overall operating state of the power station secondary system, avoiding the limitations of single subsystem features, and providing comprehensive input data for the state analysis module to build a fuzzy logic state evaluation model. The feature vector formed by fusion is delivered to the state analysis module, completing the core data output task of the data acquisition module. The feature fusion technology uses a feature-level fusion strategy to integrate scattered features from four subsystems into a unified feature vector. The technology first normalizes each feature to eliminate differences in dimension and numerical range (such as mapping different orders of magnitude of action frequency, overrun duration, etc. to the [0, 1] interval), and then integrates all features into a vector through feature splicing or weighted fusion. This fusion method can integrate the operating state information of each subsystem, avoid the limitations of single subsystem features, form a feature vector that can comprehensively reflect the overall operating state of the secondary system, and provide complete and coordinated input data for the subsequent state analysis module. Module workflow: Initialization phase: After the data acquisition module starts, it first completes hardware device self-checking, including circuit detection of each acquisition channel, function verification of the signal conditioning module, and connectivity test of the data transmission interface, to ensure that the hardware devices are operating normally without faults or abnormalities. Load preset acquisition parameters, including sampling frequency of each subsystem signal, judgment threshold of analog quantity overrun, calculation period of network time delay jitter, and extraction standard of power supply ripple coefficient, etc. Establish communication connection with the state analysis module, confirm the smoothness of the data transmission link, prepare to receive subsequent data output instructions, and complete all preparation work before module startup; Parallel acquisition stage: The module acquires the protection device action sequence signal of the protection subsystem, the analog quantity overrun signal of the measurement and control subsystem, the network time delay jitter signal of the communication subsystem, and the DC power supply ripple abnormal signal of the power supply subsystem in real time according to the preset sampling frequency through the multi-channel synchronous acquisition architecture; During the acquisition process, the timestamps of each signal are recorded in real time to ensure that the acquisition data of different subsystems remain synchronized in the time dimension and avoid timing deviation; The acquired original signals are temporarily stored in the cache area inside the module, waiting for the next processing stage; Data preprocessing stage: The acquired original signals are read from the cache area and distributed to the corresponding preprocessing channels according to the signal type, and differentiated preprocessing operations are performed on the protection device action sequence signal, analog quantity overrun signal, network time delay jitter signal, and DC power supply ripple abnormal signal, respectively; The protection device action sequence signal is subjected to action count statistics and timing alignment processing, the analog quantity overrun signal is subjected to signal validity verification and overrun amplitude classification processing, the network time delay jitter signal is subjected to time domain filtering and jitter intensity calculation processing, and the DC power supply ripple abnormal signal is subjected to frequency domain analysis and ripple coefficient extraction processing; The preprocessed signals are stored in the designated data area to prepare for the feature extraction stage; Feature extraction stage: The preprocessed signals are read from the data area, and the feature extraction program is started for signals of different subsystems; The protection action frequency feature and action logic relationship feature are extracted from the protection device action sequence signal, the overrun duration feature and overrun trend feature are extracted from the analog quantity overrun signal, the communication quality degradation feature is extracted from the network time delay jitter signal, and the power supply stability feature is extracted from the DC power supply ripple abnormal signal; All extracted features are temporarily stored in the feature cache area, waiting for feature fusion operation; Feature fusion stage: All features in the feature cache area are read, and each feature is subjected to normalization processing to eliminate the influence of dimension and numerical range difference; The normalized protection action frequency feature, action logic relationship feature, overrun duration feature, overrun change trend feature, communication quality degradation feature and power stability feature are integrated into a unified feature vector in a feature splicing manner; The integrity of the fused feature vector is checked, and after confirming that there is no feature missing or error, the feature vector is prepared for output to the state analysis module; Data output stage: The module transmits the feature vector to the state analysis module through the established communication link, and records the timestamp of data output and the key information of the feature vector, facilitating subsequent data tracing; After the output is completed, the module returns to the parallel acquisition stage and continues to collect the running state data of the four subsystems in real time, enters the next round of data processing cycle, and ensures the continuity and real-time of data acquisition.

[0019] In this embodiment, the state analysis module is the "decision core" of the lamp language system of the secondary system of the power station. It receives the feature vector output by the data acquisition module, constructs a fuzzy logic state evaluation model through multi-source information fusion, identifies abnormal patterns based on a pre-set diagnostic rule base, and finally outputs a comprehensive system state level and an abnormal event code with time stamp information, providing accurate decision basis for the lamp language mapping and generation module; Multi-source information fusion, construct a fuzzy logic-based state evaluation model, generate a preliminary system state level (divided into four levels of emergency, abnormal, attention, and normal) through standardized preprocessing, fuzzy reasoning, and de-fuzzification operations; The second part is based on the pre-set diagnostic rule base, extracts abnormal feature indicators from the feature vector and performs rule matching, generates an abnormal event code containing fault location identification and fault type identification after triggering an abnormal pattern, and performs weighted fusion combined with the preliminary system state level to determine the final comprehensive system state level; The module finally outputs the comprehensive system state level and at least one abnormal event code with time stamp information to the lamp language mapping and generation module to provide decision support for the generation of lamp language control instructions; including: Fuzzy logic state evaluation unit: Feature vector reception and standardization: receive the feature vector representing the overall running state of the secondary system delivered by the data acquisition module, and perform standardized preprocessing on the feature vector; By eliminating the differences in dimensions (such as "times / minute" of action frequency, "milliseconds" of time delay jitter) and numerical ranges of different features, the feature vector is converted into a standardized feature vector, ensuring the accuracy of subsequent fuzzy reasoning; Fuzzy set and membership degree calculation: input the normalized feature vector into a predefined fuzzy logic state assessment model; the model defines fuzzy sets (e.g. "high", "medium", "low") and corresponding membership functions for each feature (e.g. protection action frequency, out-of-limit duration); each feature's normalized value is converted into a membership degree of the corresponding fuzzy set (e.g. a feature value corresponds to a membership degree of 0.8 for "high" fuzzy set and 0.2 for "medium"); Fuzzy reasoning and defuzzification: based on a pre-defined fuzzy rule base (e.g. "if protection action frequency membership degree 'high' and out-of-limit duration membership degree 'high', then system state membership degree 'emergency'"), the membership degrees of each feature are subjected to fuzzy reasoning to calculate the fuzzy membership degrees of the secondary system for four state levels: emergency, abnormal, attention, and normal; subsequently, the fuzzy membership degrees are defuzzified by the center-of-gravity method or the maximum membership degree method to convert the fuzzy output into an accurate preliminary system state level; Preliminary level output: output the preliminary system state level obtained by defuzzification as the basis for subsequent abnormal pattern recognition and comprehensive state decision-making; Abnormal pattern recognition and comprehensive decision-making unit: Abnormal feature index extraction: receive the preliminary system state level output by the fuzzy logic state assessment unit, and extract the abnormal feature indexes corresponding to the pre-defined diagnostic rule base from the original feature vector delivered by the data acquisition module; these indexes include protection action frequency abnormal indexes (e.g. the number of actions per unit time exceeding the normal range), analog quantity out-of-limit duration abnormal indexes (e.g. the duration of out-of-limit state exceeding the threshold), network time delay jitter intensity abnormal indexes (e.g. the amplitude of jitter values exceeding the normal range), and power supply ripple coefficient abnormal indexes (e.g. the proportion of ripple coefficients exceeding the standard value); Diagnostic rule matching and abnormal triggering: match the extracted abnormal feature indexes with the rule conditions in the diagnostic rule base; the diagnostic rule base is pre-defined based on the historical fault data of the secondary system of the power plant, and each rule is associated with an abnormal feature index threshold and a corresponding abnormal pattern type (e.g. "if protection action frequency abnormal index > 5 times / min, then trigger 'protection device frequent action' abnormal pattern"); when a certain abnormal feature index exceeds the threshold defined in the rule condition, the corresponding abnormal pattern is triggered, and the accurate timestamp of the abnormal occurrence (i.e. the time tag information of the abnormal event) is recorded; Abnormal event code generation: generating an abnormal event code according to the triggered abnormal mode; wherein the fault location identification is automatically assigned based on the subsystem to which the abnormal feature indicator belongs (such as the protection action frequency abnormal indicator corresponding to the "protection subsystem" and the power supply ripple coefficient abnormal indicator corresponding to the "power supply subsystem"); the fault type identification is automatically mapped based on the type of the triggered abnormal mode (such as the "protection device frequent action" mode corresponding to the "protection action abnormal" type and the "time delay jitter exceeds the standard" mode corresponding to the "communication quality deterioration" type); Comprehensive state level determination: sorting all triggered abnormal modes according to the preset severity grading rules (such as "emergency abnormal mode weight 0.6, general abnormal mode weight 0.3"), and fusing the preliminary system state level output by the fuzzy logic state evaluation unit to perform fusion calculation; determining the final comprehensive system state level through weighted evaluation (such as "preliminary level is 'abnormal', after superimposing two emergency abnormal modes, the comprehensive level is upgraded to 'emergency'"); Result output: outputting the final comprehensive system state level and at least one abnormal event code with time tag information (including time stamp, fault location identification, fault type identification) to the light language mapping and generation module; The working process of the state analysis module is as follows: Initialization stage: After the state analysis module is started, the internal parameters are initialized, including loading the fuzzy set definition of the fuzzy logic state evaluation model, the membership function parameters, the fuzzy rule base content, and the preset parameters such as the abnormal feature indicator threshold, the abnormal mode type, and the severity weight of the diagnostic rule base; Establish communication connection with the data acquisition module and the light language mapping and generation module, confirm that the data transmission link is smooth, and prepare to receive the feature vector output by the data acquisition module; Feature vector receiving and preprocessing stage Receive the feature vector representing the overall operation state of the secondary system delivered by the data acquisition module; Standardize the feature vector for preprocessing, eliminate the dimension and numerical range differences of different features, and generate a standardized feature vector; Preliminary system state level generation stage Input the standardized feature vector into the fuzzy logic state evaluation model, and calculate the membership degree of each feature to each fuzzy set through the membership function; Based on the fuzzy rule base, the membership degrees of each feature are subjected to fuzzy reasoning to obtain the fuzzy membership degrees of the system corresponding to the four levels of emergency, abnormal, attention, and normal; De-fuzz the fuzzy membership degrees by the center of gravity method or the maximum membership degree method to generate an accurate preliminary system state level; Abnormal mode recognition stage extracting a protection action frequency anomaly index, an analog quantity overrun duration anomaly index, a network time delay jitter intensity anomaly index, and a power supply ripple coefficient anomaly index from the original feature vector; matching each anomaly feature index with a rule condition in the diagnostic rule base one by one to determine whether any index exceeds the corresponding threshold value; If an index exceeds the threshold value, the corresponding anomaly mode is triggered, the precise timestamp of the anomaly occurrence is recorded, and an anomaly event code containing the fault location identifier and the fault type identifier is generated according to the anomaly mode; Comprehensive system state level determination stage sorting all triggered anomaly modes according to the pre-set severity grading rules to determine the weight of each anomaly mode; combining the preliminary system state level with the weight of each anomaly mode for weighted fusion calculation to determine the final comprehensive system state level; Result output stage packaging the comprehensive system state level and at least one anomaly event code with time stamp information (containing timestamp, fault location identifier, and fault type identifier); outputting the packaged result to the light language mapping and generation module through a communication link to complete a state analysis process; The module returns to the "feature vector receiving and preprocessing stage" and waits for the data acquisition module to output the next round of feature vectors to realize continuous state analysis.

[0020] In this embodiment, the light language mapping and generation module is the "instruction converter" of the light language system of the secondary system of the power station. It receives the system state level and the anomaly event code output by the state analysis module, relies on the pre-stored light language coding rule base, and converts abstract state information into concrete composite light language control instructions through mapping and integration operations to provide accurate control basis for the light language presentation device. It is the core link connecting "state decision" and "light signal presentation"; The light language mapping and generation module is in communication connection with the state analysis module, and internally pre-stores a light language coding rule base. The core function is divided into three steps; the first step is to receive the comprehensive system state level (emergency, anomaly, attention, and normal four levels) and at least one anomaly event code with time stamp information (containing fault location identifier and fault type identifier) output by the state analysis module; the second step is to map the system state level to the basic light language mode containing the base color and the basic flicker frequency based on the light language coding rule base, and to map the anomaly event code to the enhanced light language elements containing the color halo parameter, the additional flicker sequence mode, and the light beam scanning direction; the third step is to perform spatio-temporal superposition (synchronous flickering rule in time and color and scanning direction in space) on the basic light language mode and the enhanced light language elements to generate a composite light language control instruction that can accurately represent the system state, and finally output the instruction to the light language presentation device; including: Data receiving and initialization unit: Data receiving: Through the preset communication link, two types of core data from the state analysis module are received, namely, comprehensive system state level (such as "emergency", "normal") and at least one abnormal event code with time information (such as "protection subsystem-protection action abnormal-202510161000", containing fault location, fault type and time information); Data verification: The integrity of the received data is verified to confirm that the system state level belongs to one of the four categories of "emergency", "abnormal", "attention" and "normal", the abnormal event code contains complete fault location identification, fault type identification and time information, if the data is missing or the format is incorrect, the data retransmission request is triggered to ensure the validity of the input data; Control data structure initialization: A light language control data structure is created and initialized, which includes "basic light language parameter area" (reserved base color, basic flicker frequency field) and "enhanced light language parameter area" (reserved color halo parameter, additional flicker sequence mode, beam scanning direction field), providing a standardized data container for subsequent parameter filling; Basic light language mode mapping unit: Rule library query: The internally pre-stored light language coding rule library is called to match the corresponding mapping rules according to the received system state level; the light language coding rule library predefines a one-to-one correspondence between "system state level-basic light language parameters" (such as "emergency" level corresponding to "red base color+2Hz basic flicker frequency", "normal" level corresponding to "green base color+0.5Hz basic flicker frequency"); Parameter extraction and filling: The base color (such as RGB three primary color matching value) and the basic flicker frequency (such as the number of on-off times per unit time) are extracted from the matched rules, and the two types of parameters are filled into the "basic light language parameter area" of the light language control data structure to form a complete basic light language mode, which is used to intuitively reflect the severity of the overall system operation state; Enhanced light language element mapping unit: Abnormal event code analysis: The received abnormal event code is disassembled to extract the fault location identification (such as "protection subsystem" "power subsystem") and fault type identification (such as "protection action abnormal" "ripple exceeds standard"), and the time information (time is only used for event tracing and does not participate in light language mapping) is ignored; Multi-dimensional rule matching: The light language coding rule library is queried again based on the pre-defined rules of "fault location identification-beam scanning direction" and "fault type identification-color halo parameter / additional flicker sequence mode" for matching; for example, "protection subsystem" corresponds to "analog screen left area beam scanning direction", and "ripple exceeds standard" corresponds to "yellow halo parameter+1.5Hz additional flicker sequence mode"; Enhancement parameter filling: Fill the matched color halo parameters (such as halo color, gradient amplitude), additional flicker sequence patterns (such as flicker interval, duration), beam scanning direction (such as area pointing on the analog screen, deflection angle) into the "enhanced light language parameter area" of the light language control data structure to form an enhanced light language element. This element is used to accurately supplement the abnormal position and type information; Space-time integration and instruction generation unit: Time dimension integration: Synchronize the arrangement of the basic flicker frequency and the additional flicker sequence pattern in the light language control data structure; according to the pre-defined timing rules, superimpose the additional flicker sequence pattern on the basic flicker frequency to ensure their coordination in time (such as the basic flicker frequency is 2Hz, the additional flicker sequence pattern is embedded according to the rule of "on for 0.2 seconds, off for 0.3 seconds", forming a composite flicker timing of "basic frequency + additional rule"), avoiding timing conflicts; Space dimension integration: Color fusion of base color and color halo parameters, according to the color superposition rule to generate a composite color with base color and halo effect (such as red base color superimposed with yellow halo, forming a visual effect of "red base yellow halo"); combined with the beam scanning direction, determine the spatial pointing path of the composite color beam on the analog screen (such as the "red base yellow halo" beam scanning along the left area of the analog screen), and clarify the spatial pointing nature; Composite instruction generation: Integrate the composite flicker timing after time integration, the composite color and scanning path after space integration into a unified composite light language control instruction. The instruction contains the driving parameters (color ratio, flicker timing) of the RGB-LED array and the control parameters (scanning direction, deflection angle) of the beam deflection mechanism, ensuring that the light language presentation device can be directly parsed and executed; Instruction output verification: After format verification of the generated composite light language control instruction, confirm the parameter completeness and logic correctness, and output to the light language presentation device through the communication link; The space-time integration and instruction generation unit solves the coordination problem of the basic light language mode and the enhanced light language element, which is divided into two dimensions of time and space. Time integration is based on timing synchronization rules. By analyzing the period and duty cycle of the basic flicker frequency and the additional flicker sequence pattern, the superposition strategy is developed to ensure that the additional sequence does not destroy the core rhythm of the basic frequency, while highlighting the abnormal prompt. Space integration is based on color fusion and spatial pointing rules. Through the RGB color mixing algorithm, the natural superposition of base color and halo is realized. Combined with the area division of the analog screen, the scanning direction is determined to ensure that the light signal can reflect both "overall state" and "abnormal position" in space, forming a "space-time coordinated" composite light signal logic; The workflow of the light language mapping and generation module is as follows: Initialization phase: After the lamp language mapping and generation module is started, the internal pre-stored lamp language coding rule library is loaded, and it is confirmed that the mapping rules of "state level-basic parameters" and "fault information-enhanced parameters" in the rule library are complete and have no missing; The communication connection with the state analysis module and the lamp language presentation device is established, the smoothness of the data transmission link is tested, and the format standard of the instruction output (such as the parameter coding mode and the transmission baud rate) is set; The internal data processing buffer area is initialized, the historical data is emptied, and it is ensured that the new data reception and processing are not disturbed; Data reception and verification stage: Receive the comprehensive system state level and at least one abnormal event code with time stamp information output by the state analysis module; Integrity and validity verification is performed on the received data: check whether the system state level belongs to the pre-set four types, whether the abnormal event code contains the fault location, fault type and time stamp; if the verification fails, send a data retransmission request to the state analysis module until the valid data is received; Initialize the lamp language control data structure, create the "basic lamp language parameter area" and the "enhanced lamp language parameter area"; Basic lamp language mode mapping stage: Query the lamp language coding rule library, and match the corresponding basic lamp language mapping rule according to the system state level; Extract the base color (such as RGB value 255, 0, 0 corresponding to red) and the basic flicker frequency (such as 2 Hz corresponding to 2 times on-off per second) from the matched rule; Fill the base color and the basic flicker frequency into the "basic lamp language parameter area" of the lamp language control data structure, and complete the basic lamp language mode construction; Enhanced lamp language element mapping stage: Parse the abnormal event code, extract the fault location identifier (such as "communication subsystem") and the fault type identifier (such as "time delay jitter exceeds the standard"); Query the lamp language coding rule library, match the corresponding light beam scanning direction according to the fault location identifier (such as "communication subsystem" corresponding to "horizontal scanning in the middle area of the analog screen"), and match the corresponding color halo parameter (such as "time delay jitter exceeds the standard" corresponding to "blue halo, gradient amplitude 50%") and additional flicker sequence mode (such as "1.5 Hz, on for 0.2 seconds and off for 0.3 seconds") according to the fault type identifier; Fill the color halo parameter, additional flicker sequence mode and light beam scanning direction into the "enhanced lamp language parameter area" of the lamp language control data structure, and complete the enhanced lamp language element construction; Time and space integration and instruction generation stage: Time integration: synchronize the base flicker frequency with the additional flicker sequence pattern to generate a composite flicker timing (e.g., in a base 2Hz flicker, embed an additional 1.5Hz flicker once every 2 periods); Space integration: integrate the base color with the color halo parameters through a color mixing algorithm to generate a composite color; determine the spatial scanning path of the composite color beam in combination with the beam scanning direction; Integrate the composite flicker timing, composite color parameters, and beam scanning path into a composite light language control instruction, which contains complete control parameters for the RGB-LED array and beam deflection mechanism; Instruction output stage: Format check the composite light language control instruction to confirm that the parameters are complete and the logic is conflict-free; Output the instruction to the light language presentation device through the communication link, and record the instruction generation time and corresponding system state level, abnormal event code for subsequent tracing; The module returns to the "data receiving and verification stage" and waits for the state analysis module to output the next round of data, realizing continuous generation of light language control instructions.

[0021] In this embodiment, the light language presentation device is the "light signal output terminal" of the power station secondary system light language system, which receives the composite light language control instruction output by the light language mapping and generation module, and presents a dynamic light signal with spatial directionality on the large analog screen in the main control room of the power station through driving multiple groups of light sources containing RGB-LED arrays and beam deflection mechanisms, converting abstract system state and abnormal information into intuitive and recognizable visual signals, and is the core hardware carrier for realizing "state visualization"; The light language presentation device is connected with the light language mapping and generation module, and the core function is divided into four steps; the first step is to receive the composite light language control instruction, which contains the base light language mode parameters (base color, base flicker frequency) and enhanced light language element parameters (color halo parameters, additional flicker sequence pattern, beam scanning direction); the second step is to analyze the instruction and extract various control parameters; the third step is to convert the parameters into driving signals for the RGB-LED array and control instructions for the beam deflection mechanism, realizing color fusion of the base color and halo, time sequence synthesis of the base and additional flicker, and precise control of the beam scanning direction; the fourth step is to synchronously drive the RGB-LED array and the beam deflection mechanism, through the cooperative work of multiple groups of light sources, to form a dynamic light signal with spatial directionality (represented by beam scanning trajectory and stopping position) on the large analog screen, allowing the main control room personnel to intuitively grasp the running state and abnormal information of the power station secondary system; the light language presentation device executes the following processing flow to realize the generation and presentation of dynamic light signals: Receiving the composite light language control instruction from the light language mapping and generating module, and analyzing the instruction to extract the basic light language mode parameters and enhanced light language element parameters contained therein; Converting the analyzed basic light language mode parameters into driving signals for the RGB-LED array, wherein the base color parameters correspond to the RGB primary color ratio values, and the basic flashing frequency parameters correspond to the periodic on-off timing of the LED light source; According to the color halo parameter in the enhanced light language element, superimposing additional color effects on the base color of the basic light language mode to generate a halo control signal with color gradient levels; Time sequence synthesis of the additional flashing sequence mode and the basic flashing frequency to form an integrated flashing control signal containing a composite flashing rule; Converting the light beam scanning direction parameter into a control instruction for the light beam deflection mechanism to determine the dynamic scanning path of the light beam emitted by the RGB-LED array on the large simulation screen; Synchronously driving the RGB-LED array and the light beam deflection mechanism so that the RGB-LED array emits a light beam with specific color, flashing rule and halo effect according to the integrated flashing control signal and the halo control signal, while the light beam deflection mechanism guides the light beam to deflect along the specified scanning path according to the control instruction; Through the cooperative work of multiple groups of light sources, a dynamic light signal with spatial directivity is formed on the large simulation screen, wherein the spatial directivity is represented by the scanning trajectory and stopping position of the light beam on the simulation screen; Further, the light language presentation device comprises: Instruction analysis unit: Instruction reception: receiving the composite light language control instruction from the light language mapping and generating module through the preset communication interface to ensure the stability and integrity of the instruction transmission; Parameter extraction: analyzing the received composite light language control instruction, separating and extracting the basic light language mode parameters and enhanced light language element parameters; the basic light language mode parameters include the RGB primary color ratio values corresponding to the base color, and the periodic on-off timing parameters corresponding to the basic flashing frequency; the enhanced light language element parameters include the color halo parameter (halo color, gradient amplitude), the additional flashing sequence mode parameter (flashing interval, duration), and the light beam scanning direction parameter (region pointing on the simulation screen, deflection angle); Parameter verification: verifying the effectiveness of the extracted parameters to confirm that the RGB color ratio value is within the range of 0-255, the flashing frequency conforms to the hardware driving capability, and the light beam scanning direction is within the effective display area of the simulation screen; if the parameters exceed the reasonable range, feedback the parameter abnormal information to the light language mapping and generating module, and request to resend the instruction to ensure the safety and accuracy of subsequent hardware driving; RGB-LED array driving unit: Basic driving signal conversion: convert the parsed basic light language mode parameters into the basic driving signals of the RGB-LED array; wherein the RGB three-primary color matching value of the basic color is converted into the current control signal of the LED chip, and the current proportion of the red, green and blue three-color LEDs is adjusted to realize the accurate presentation of the preset basic color; the basic flicker frequency parameter is converted into the periodic on-off timing signal of the LED light source, and the RGB-LED array is controlled to cycle on-off at the set frequency; Halo effect generation: according to the colored halo parameter in the enhanced light language element, superimpose the additional color effect on the basic color of the basic light language mode; through the color mixing algorithm, the RGB value corresponding to the halo color and the RGB value of the basic color are fused and calculated to generate a halo control signal with color gradient levels, and then the signal is superimposed into the basic driving signal, so that the RGB-LED array emits composite light with basic color and halo effect; Flicker timing synthesis: time sequence synthesis of the additional flicker sequence mode in the enhanced light language element and the basic flicker frequency; according to the flicker interval and duration parameters of the additional flicker sequence mode, the additional flicker logic is embedded in the cycle of the basic flicker timing to form an integrated flicker control signal containing "basic frequency + additional rule", ensuring that the two flicker modes cooperate without conflict, while highlighting the abnormal prompt effect; Array driving: integrate the color driving signal with the fused halo effect and the synthesized integrated flicker control signal, and output to the driving circuit of the RGB-LED array to control multiple RGB-LED light sources to emit light according to the set color and flicker rule; The RGB-LED array driving unit is based on the three-primary color mixing theory and realizes color presentation by accurately controlling the luminous intensity of RGB three-color LEDs; the RGB-LED array is composed of red, green and blue single-color LED chips, and the current and luminous intensity of each color LED chip are linearly related; the technical core is to convert the RGB matching value of the basic color and the halo into the current control signal of the corresponding color LED, adjust the current size to change the intensity of monochromatic light, and then use the visual color mixing effect of the human eye to make the three-color light mixed to present the preset basic color or "basic color + halo" composite color; for example, when the basic color is red (RGB: 255, 0, 0) and the halo is yellow (RGB: 255, 255, 0), the visual effect of red bottom yellow halo is formed by adjusting the full current of the red LED and the half current of the green LED. Light beam deflection mechanism control unit: Scan direction conversion: convert the extracted beam scanning direction parameters (analog screen area pointing, deflection angle) into mechanical control instructions of the beam deflection mechanism; the beam deflection mechanism is built-in with a stepper motor or a servo motor, and the control instructions determine the dynamic scanning path of the light beam emitted by the RGB-LED array on the large analog screen by adjusting the rotation angle and speed of the motor; Path planning: according to the beam scanning direction parameters, combined with the size and partition information of the large analog screen, the specific scanning trajectory of the light beam is planned; for example, if the beam scanning direction parameter points to "the left area of the analog screen corresponding to the protection subsystem", a linear scanning trajectory from the left edge of the analog screen to the center of the area is planned, and the dwell time at the center of the area is set to strengthen the spatial directivity; Mechanism driving: convert the planned scanning path into pulse control signals of the motor to drive the motor of the beam deflection mechanism to rotate according to the set trajectory, guide the light beam emitted by the RGB-LED array to deflect along the specified scanning path on the analog screen, and realize precise control of the spatial directivity of the light beam; The beam deflection mechanism control unit realizes precise control of the beam scanning direction based on motor driving and position feedback mechanism; the core of the beam deflection mechanism is a stepper motor or a servo motor, and the rotation angle of the motor is proportional to the pulse number of the pulse control signal, and the speed is proportional to the pulse frequency; the technical process is: first, convert the deflection angle of the beam scanning direction into the pulse number required by the motor, and convert the scanning speed into the pulse frequency; then send the pulse control signal to the motor through the motor driver to drive the motor to rotate the optical deflection component (such as a mirror); at the same time, the position sensor built-in the motor feedbacks the actual rotation angle in real time, compares it with the preset angle, corrects the deviation through closed-loop control, ensures that the light beam can deflect precisely along the set scanning path on the analog screen, and realizes accurate presentation of spatial directivity; Cooperative control unit: Timing synchronization: receive the integrated flashing control signal of the RGB-LED array driving unit and the motor pulse control signal of the beam deflection mechanism control unit, and synchronize and calibrate the timing of the two; ensure that the flashing change of the RGB-LED array and the scanning action of the beam deflection mechanism are consistent, for example, when the light beam scans to a specific abnormal area of the analog screen, trigger the additional flashing sequence synchronously to strengthen the visual prompt effect of the abnormal position; Multi-light source cooperative scheduling: if the device contains multiple groups of RGB-LED arrays and corresponding beam deflection mechanisms, the cooperative control unit will schedule different groups of light sources to work according to the beam scanning direction parameters in the instructions; for example, when multiple subsystems appear abnormal at the same time, the RGB-LED arrays corresponding to the areas control the light signals to match the abnormalities respectively, avoid the interference of multiple groups of light sources, and ensure the clarity of information transmission; State feedback: Real-time monitoring of the light-emitting state of the RGB-LED array (such as whether it is normally on and off, and whether the color is deviated) and the running state of the light beam deflection mechanism (such as whether the motor is stuck, and whether the scanning position is accurate), and the state information is fed back to the main control unit, so that personnel can timely find hardware faults and ensure the continuous and stable operation of the device; The flickering timing synchronization technology is based on timing logic control to realize the collaborative synthesis of basic flickering and additional flickering. The technical core is to build a timing control module, taking the period corresponding to the basic flickering frequency as the main timing period, and dividing the secondary timing period according to the parameters (flickering interval, duration) of the additional flickering sequence mode in the main period. For example, the basic flickering period is 0.5 seconds (frequency 2Hz), and the additional flickering sequence is "on for 0.2 seconds, off for 0.3 seconds". In each basic flickering period, an additional flickering secondary timing is embedded, so that the RGB-LED array realizes more complex flickering effects according to the additional rules while the basic on-off is implemented. At the same time, the timing control module is linked with the scanning timing of the light beam deflection mechanism to ensure that the flickering changes and the light beam scanning actions are synchronized, avoiding visual information misplacement. The working process of the light language presentation device is as follows: Initialization phase: After the light language presentation device is started, hardware self-checking is completed, including the light-emitting test of each LED chip of the RGB-LED array, the no-load rotation test of the motor of the light beam deflection mechanism, and the communication interface test of the instruction analysis unit, to confirm that each hardware module is fault-free and functions normally. Load hardware parameter configuration, set the maximum driving current of the RGB-LED array, the maximum rotation angle and rotation speed limit of the light beam deflection mechanism, and the coordinate range of the effective display area of the simulation screen, to provide hardware boundary basis for subsequent parameter analysis and driving. Establish communication connection with the light language mapping and generation module, confirm that the communication protocol is matched and the data transmission rate is consistent, and enter the instruction receiving ready state. Instruction receiving and analysis phase: The instruction analysis unit receives the composite light language control instruction through the communication interface and stores it in the temporary buffer area. Analyze the instructions in the buffer area, extract the basic light language mode parameters (RGB ratio, basic flickering frequency) and enhanced light language element parameters (halo parameters, additional flickering parameters, scanning direction parameters). Perform validity check on the extracted parameters to confirm that the parameters meet the hardware configuration requirements. If the check is passed, proceed to the next stage. If the check fails, feedback the abnormal information and wait for the instruction to be received again. Drive signal and control instruction generation phase: The RGB-LED array driving unit converts the primary color RGB proportion into a current control signal and converts the basic flicker frequency into an on-off timing signal; then combines the color halo parameter to generate a halo control signal, which is fused with the basic current control signal; at the same time, the additional flicker parameter is combined to generate an additional timing signal, which is synthesized with the basic on-off timing signal to form an integrated driving signal; The light beam deflection mechanism control unit converts the light beam scanning direction parameter into a motor pulse control signal, plans the scanning path in combination with the analog screen area information, determines the motor rotation angle and speed, and generates complete mechanism control instructions; Synchronous driving and light signal presentation stage: The cooperative control unit receives the integrated driving signal of the RGB-LED array and the control instructions of the light beam deflection mechanism, synchronizes and calibrates the time sequences of the two, and ensures the cooperation of flickering and scanning actions; The integrated driving signal is output to the RGB-LED array driving circuit to control multiple groups of RGB-LED light sources to emit light according to the set color and flickering rule; at the same time, the control instructions are output to the light beam deflection mechanism to drive the motor to rotate the optical components and guide the light beam to scan along the planned path on the analog screen; Through the cooperative work of multiple light sources, a dynamic light signal with spatial directivity is formed on the large analog screen, and the spatial directivity is represented by the scanning track (such as pointing to the corresponding area of the protection subsystem) and the stopping position (such as temporarily stopping at the abnormal position) of the light beam; State monitoring and feedback stage: The cooperative control unit monitors the light-emitting state of the RGB-LED array and the running state of the light beam deflection mechanism in real time, and records abnormal information (such as LED not lighting, motor jamming); The device running state information is fed back to the lamp language mapping and generation module at regular intervals, and if a hardware failure is detected, a failure alarm is immediately sent to facilitate the maintenance personnel to timely troubleshoot and repair, and to ensure the continuous and stable work of the device.

[0022] Although embodiments of the present application have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the present application, and the scope of the present application is defined by the appended claims and their equivalents.

Claims

1. A lamp code system for a power plant secondary system, characterized by: Comprise: A data acquisition module for acquiring real-time operation state data of the protection, measurement and control, communication and power supply four subsystems in the secondary system of the power plant, the operation state data including the action sequence signal of the protection device, the analog quantity overrun signal of the measurement and control device, the network time delay jitter signal of the communication network and the ripple abnormal signal of the power supply system; A state analysis module in communication connection with the data acquisition module, for multi-source information fusion on the operation state data to establish a state evaluation model based on fuzzy logic, and identifying abnormal patterns in the operation state data based on a pre-set diagnostic rule base, outputting a comprehensive system state level and at least one abnormal event code with time information; wherein the system state level is divided into four levels of emergency, abnormal, attention and normal, and the abnormal event code contains fault location identification and fault type identification; A light language mapping and generating module in communication connection with the state analysis module and internally pre-storing a light language coding rule base; for receiving the system state level and the abnormal event code, querying the light language coding rule base to map the system state level into a basic light language mode containing base colors and a basic flickering frequency, and map the abnormal event code into enhanced light language elements containing color light halo parameters, additional flickering sequence modes and light beam scanning directions, and then superimpose the basic light language mode and the enhanced light language elements in time and space to generate a composite light language control instruction; A light language presentation device connected with the light language mapping and generating module, for receiving the composite light language control instruction and driving multiple groups of light sources containing RGB-LED arrays and light beam deflection mechanisms to present dynamic light signals with spatial directivity on a large analog screen in the main control room of the power plant; wherein the spatial directivity is realized by controlling the light beam scanning direction through the light beam deflection mechanism.

2. A lamp-lingo system for a power plant secondary system according to claim 1, characterized in that: The data acquisition module is used for acquiring real-time operation state data of the protection, measurement and control, communication and power supply four subsystems in the secondary system of the power plant, comprising: Parallelly acquiring the protection device action sequence signal of the protection subsystem, the analog quantity overrun signal of the measurement and control subsystem, the network time delay jitter signal of the communication subsystem and the DC power supply ripple abnormal signal of the power supply subsystem; Performing action number statistics and time sequence alignment processing on the acquired protection device action sequence signal, signal effectiveness verification and overrun amplitude classification processing on the analog quantity overrun signal, time domain filtering and jitter intensity calculation processing on the network time delay jitter signal, and frequency domain analysis and ripple coefficient extraction processing on the DC power supply ripple abnormal signal; Extracting protection action frequency features and action logic relationship features based on the preprocessed action sequence signal, extracting overrun duration features and overrun trend features based on the preprocessed analog quantity overrun signal, extracting communication quality degradation features based on the preprocessed network time delay jitter signal, and extracting power supply stability features based on the preprocessed DC power supply ripple abnormal signal; The extracted protection action frequency features, action logic relationship features, out-of-limit duration features, out-of-limit change trend features, communication quality degradation features and power supply stability features are fused at a feature level to form a feature vector representing the overall operation state of the power station secondary system; The feature vector is transmitted to a state analysis module as input data of a fuzzy logic-based state evaluation model.

3. The lampoon system of a power plant secondary system according to claim 1, characterized by: The state analysis module is configured to perform multi-source information fusion on the operation state data to establish the fuzzy logic-based state evaluation model, and includes: receiving the feature vector transmitted by the data acquisition module; performing standardization preprocessing on the feature vector to eliminate differences in dimensions and numerical ranges of different features, and generating a standardized feature vector; inputting the standardized feature vector into a predefined fuzzy logic state evaluation model, wherein the fuzzy logic state evaluation model includes fuzzy sets and membership functions defined for each feature, for converting each feature value into a membership degree of the corresponding fuzzy set; performing fuzzy reasoning on the membership degrees based on a preconfigured fuzzy rule base, and calculating fuzzy membership degrees of the power station secondary system corresponding to four state levels of emergency, abnormality, attention and normality; performing defuzzification processing on the fuzzy membership degrees, and converting the fuzzy output into an accurate preliminary system state level by using a barycenter method or a maximum membership degree method; outputting the preliminary system state level as a basis for abnormal pattern recognition and comprehensive state decision.

4. The lampoon system of a power plant secondary system according to claim 1, characterized by: The state analysis module identifies abnormal patterns in the operation state data based on a preconfigured diagnostic rule base, and outputs a comprehensive system state level and at least one abnormal event code with timestamp information, and includes: receiving the preliminary system state level; extracting abnormal feature indicators corresponding to the preconfigured diagnostic rule base from the feature vector, wherein the abnormal feature indicators include protection action frequency abnormal indicators, analog quantity out-of-limit duration abnormal indicators, network time delay jitter intensity abnormal indicators and power supply ripple coefficient abnormal indicators; matching the abnormal feature indicators with rule conditions in the diagnostic rule base item by item, wherein the diagnostic rule base contains rules predefined based on historical fault data of the power station secondary system, each rule is associated with an abnormal feature indicator threshold and a corresponding abnormal pattern type; triggering the corresponding abnormal pattern when the abnormal feature indicator exceeds the threshold defined in the rule condition, and recording the accurate timestamp of the abnormal occurrence; generating an abnormal event code according to the triggered abnormal pattern, wherein the fault location is automatically assigned based on the subsystem to which the abnormal feature indicator belongs, and the fault type is automatically mapped based on the triggered abnormal pattern type; sorting all triggered abnormal patterns according to preconfigured severity grading rules, and performing fusion calculation in combination with the preliminary system state level to determine the final comprehensive system state level through weighted evaluation; outputting the comprehensive system state level and at least one abnormal event code with timestamp information to a light language mapping and generation module.

5. The lampoon system of a power plant secondary system according to claim 1, characterized by: The light language mapping and generation module is configured to receive the system state level and the abnormal event code, and generate a composite light language control instruction, and includes: receive the system state level and at least one abnormal event code with time stamp information from the state analysis module, and initialize a light language control data structure; query the pre-stored light language coding rule library, map the corresponding base color and basic flashing frequency according to the system state level, and set the base color and basic flashing frequency to the light language control data structure to form a basic light language mode; based on the processed light language control data structure, query the light language coding rule library, map the corresponding color halo parameters, additional flashing sequence mode and light beam scanning direction according to the fault location identifier and fault type identifier in the abnormal event code, and add these enhanced light language elements to the light language control data structure; temporal and spatial integration of the basic light language mode and enhanced light language elements in the processed light language control data structure, wherein the temporal integration includes synchronously arranging the basic flashing frequency and the additional flashing sequence mode, and the spatial integration includes fusing the base color and the color halo parameters and determining the spatial directivity through the light beam scanning direction, thereby generating a composite light language control instruction.

6. The lampoon system of a power plant secondary system according to claim 1, characterized by: The light language presentation device performs the following processing flow to realize the generation and presentation of dynamic light signals: receive the composite light language control instruction from the light language mapping and generation module, and analyze the instruction to extract the basic light language mode parameters and enhanced light language element parameters contained therein; convert the basic light language mode parameters obtained by analysis into driving signals of the RGB-LED array, wherein the base color parameter corresponds to the ratio value of the RGB three primary colors, and the basic flashing frequency parameter corresponds to the periodic on-off timing of the LED light source; according to the color halo parameters in the enhanced light language elements, superimpose additional color effects on the basis of the base color of the basic light language mode to generate a halo control signal with color gradient levels; time sequence synthesis of the additional flashing sequence mode and the basic flashing frequency to form an integrated flashing control signal containing a composite flashing rule; convert the light beam scanning direction parameter into a control instruction of the light beam deflection mechanism to determine the dynamic scanning path of the light beam emitted by the RGB-LED array on the large simulation screen; synchronously drive the RGB-LED array and the light beam deflection mechanism, so that the RGB-LED array emits a light beam with specific color, flashing rule and halo effect according to the integrated flashing control signal and the halo control signal, while the light beam deflection mechanism guides the light beam to deflect along the specified scanning path according to the control instruction; through the cooperative work of multiple groups of light sources, a dynamic light signal with spatial directivity is formed on the large simulation screen, wherein the spatial directivity is represented by the scanning track and the stopping position of the light beam on the simulation screen.

Images