A composite fire detector detection experiment host and a detection method thereof

Abstract

The present application relates to a kind of composite fire detector detection experiment host and its detection method, belong to fire detection technical field.The method includes: obtaining smoke, temperature, combustible gas associated optical signal, resistance fluctuation signal, current signal, and is amplified, noise reduction optimization processing, integration is converted into unified digital signal, simultaneously the digital signal is converted into characteristic parameter quantization value, generates standardization detection data by data standardization optimization mechanism;Through the construction of multi-parameter threshold matching model, output detection determination signal and linkage signal, build hierarchical alarm strategy and output early warning signal and active drive signal.Multiple signal fusion detection and intelligent hierarchical alarm are realized, the accuracy of composite fire detector detection, response efficiency are improved, reliable experimental support and technical support are provided for fire detection work.

Description

Technical Field

[0001] This invention belongs to the field of fire protection testing technology, specifically relating to a composite fire detector testing experimental host and its testing method. Background Technology

[0002] The accuracy of fire detection directly determines the effectiveness of fire prevention and control. Given the diverse causes and complex development processes of fires in various building and industrial settings, fire detectors that only detect smoke, temperature, or combustible gases are prone to missed or false alarms due to their limited detection dimensions. Therefore, integrated multi-parameter detection composite fire detectors have become the mainstream application. The accuracy and reliability of factory performance testing and on-site calibration of composite fire detectors directly affect their actual fire detection performance. Thus, specialized testing and experimental technologies adapted to composite fire detectors have become an important research and development direction in the fire protection testing field. The industry has placed higher demands on their capabilities for simultaneous multi-parameter detection, accurate signal processing, and intelligent alarm judgment.

[0003] Current fire detector testing technologies still have many shortcomings in adaptability, making it difficult to meet the testing requirements of composite fire detectors. On the one hand, existing technologies are mostly designed for single-type fire detectors, focusing on the acquisition and simple processing of single sensor signals, lacking the ability to simultaneously acquire and coordinate the processing of smoke optical signals, temperature resistance fluctuation signals, and combustible gas current signals from composite detectors. On the other hand, there is a lack of targeted design for processing sensor signals with different characteristics. Combustible gas current signals are not amplified and interference suppressed in stages according to amplitude differences, and the noise reduction processing of smoke optical signals and temperature resistance fluctuation signals does not incorporate dedicated logic designed to address the inherent interference characteristics of the signals. This easily leads to distortion and noise interference during signal transmission and processing, insufficient extraction of effective feature information, and a significant reduction in the accuracy of subsequent signal quantization and conversion.

[0004] On the other hand, the parameter determination and alarm control logic design of existing detection technologies are imperfect. Multi-parameter threshold matching only uses a single-parameter independent comparison method, without constructing a collaborative matching model for temperature, smoke, and combustible gases based on the fire development pattern. Furthermore, the threshold settings are fixed and cannot be dynamically adjusted according to different application scenarios, easily leading to missed and false alarms in fire detection. The graded alarm strategy is out of touch with actual fire prevention and control needs. The alarm level triggering logic does not distinguish between single-parameter anomalies and multi-parameter collaborative anomalies, and the generation of linkage signals also lacks unified standards. In addition, in existing detection technologies, there is no unified format standard for the conversion of different types of sensor signals. The data standardization processing lacks system error correction and abnormal data screening mechanisms, and the poor connection between various processing links leads to insufficient accuracy and comparability of detection data, making it difficult to meet the standardized and high-precision detection experimental requirements of composite fire detectors.

[0005] In summary, the existing technology lacks a testing host and testing method that can achieve targeted processing of multi-type sensor signals from composite fire detectors, multi-parameter collaborative threshold matching, and design of scientific hierarchical alarm and linkage control logic. This restricts the standardization and precision development of composite fire detector testing experiments. There is an urgent need to propose a new composite fire detector testing experimental technology solution to solve the above-mentioned problems in the existing technology. Summary of the Invention

[0006] To address the aforementioned problems in the existing technology, this invention provides a composite fire detector testing experimental host and its testing method.

[0007] The objective of this invention can be achieved through the following technical solution: a composite fire detector testing experimental host and its testing method, comprising: S1: Obtain the optical signal triggered by smoke particles, obtain the resistance fluctuation signal based on the correlation between temperature and sensing characteristics, and obtain the current signal through the electrochemical, catalytic combustion and semiconductor reaction between combustible gas and sensing material. S2: The current signal is amplified and optimized, the optical signal and the resistance fluctuation signal are denoised, and an initial analog signal is generated. The initial analog signal is normalized into a digital signal of a unified format through circuit adaptation and conversion. At the same time, the digital signal is converted into the quantized value of the feature parameter. A data standardization optimization mechanism is adopted to generate standardized detection data. S3: Construct a multi-parameter threshold matching model, compare the standardized detection data with the preset threshold, output the matching result, generate the corresponding detection judgment signal, output the detection judgment signal through the bus communication mechanism, and synchronously generate a linkage signal that can trigger subsequent alarm actions. S4: Based on the detection and judgment signal and the linkage signal, construct a hierarchical alarm strategy and output early warning signal and active drive signal.

[0008] Specifically, the process of amplifying and optimizing the current signal is as follows: first, the source characteristics of the current signal are identified, a hierarchical amplification logic is adopted, the amplification gain is dynamically adjusted according to the amplitude difference of the current signal generated by the reaction of combustible gas, an interference suppression mechanism is integrated during the amplification process, environmental factors and noise interference introduced by the signal transmission link are filtered out, and the amplified current signal is converted into a stable electrical signal form required for subsequent quantization through signal form adaptation processing.

[0009] Specifically, the noise reduction process for the optical signal and the resistance fluctuation signal is as follows: First, distinguish the interference differences between the optical signal and the resistance fluctuation signal; based on the optical signal, reduce the intrusion of ambient stray light by utilizing the light-shielding protection effect of the closed detection structure, and then perform filtering to filter out noise that exceeds the effective signal range; based on the resistance fluctuation signal, based on the inherent correlation between temperature and resistance, extract the effective fluctuation that corresponds to temperature changes through characteristic correlation filtering logic, and eliminate disordered interference signals without temperature correlation; and then perform smoothing processing on the optical signal and the resistance fluctuation signal respectively.

[0010] Specifically, the process of integrating and generating the initial analog signal is as follows: classifying and identifying the processed optical signal, the resistance fluctuation signal, and the current signal; eliminating signal format differences through a signal adaptation link; and then using the logic of classification, aggregation, and synchronous integration to perform collaborative aggregation and generate the initial analog signal.

[0011] Specifically, the process of normalizing the initial analog signal into a unified digital signal through circuit adaptation and conversion is as follows: First, the characteristic differences of the optical signal, the resistance fluctuation signal, and the current signal are identified, and the parameter adaptability of the signals is adjusted through the adaptation link to eliminate the inherent differences of the initial analog signal; then, signal discretization conversion logic is used to convert the parameter-adjusted initial analog signal into a discretized digital form; the format of the discretized digital signal is normalized to unify the signal transmission specifications, data structure, and parameter type identification; and the distorted signal in the conversion process is eliminated through signal validity verification.

[0012] Specifically, the process of converting the digital signal into a quantized value of the feature parameter is as follows: first, identify the fire feature parameter type corresponding to the digital signal, match the characteristic correlation law corresponding to the detection principle, and convert it according to the preset signal-parameter correspondence benchmark to generate the quantized value of the feature parameter.

[0013] Specifically, the data standardization and optimization mechanism includes: calibrating and correcting the quantized values ​​of the feature parameters based on the detection principle and signal characteristics of the feature parameters to offset system errors; uniformly adapting the quantized values ​​corresponding to smoke concentration, temperature, and combustible gas concentration to the metrological specifications for subsequent processing to eliminate differences in the original measurement methods of the parameters; standardizing the data structure and transmission format of the quantized values; and simultaneously filtering out abnormal and distorted data based on the reasonable variation range and inherent laws of the feature parameters to generate the standardized detection data.

[0014] Specifically, the process of constructing the multi-parameter threshold matching model is as follows: based on the standardized detection data, a corresponding threshold is set, and the threshold is dynamically adjusted according to the differences in application scenarios; a core matching logic is constructed, namely single-parameter threshold matching, which compares the standardized detection data with the corresponding preset threshold to determine the compliance status of a single parameter; composite-parameter threshold matching, which associates the temperature parameter with other feature parameters to determine the overall compliance status; and data validity verification logic is used to eliminate abnormal and distorted data.

[0015] Specifically, the process of generating the corresponding detection and judgment signal is as follows: based on the matching result, the received matching result is parsed for type, and then the corresponding alarm logic and normal monitoring status are associated according to the parsed result type. For the alarm-type detection and judgment signal to be generated, key identification information is embedded. The single parameter type identifier and the first-level alarm attribute identifier are added to the first-level alarm signal, and the parameter type identifier and the second-level alarm attribute identifier are added to the second-level alarm signal. The generated detection and judgment signal is structurally optimized according to the transmission specification, and the signal transmission format, data encoding and identification rules are unified to generate the detection and judgment signal.

[0016] Specifically, the process of synchronously generating the linkage signal that can trigger subsequent alarm actions is as follows: the alarm attributes of the detection and judgment signal are analyzed, the secondary alarm signal is identified, and the linkage signal is generated according to the preset linkage signal output specifications and in combination with the activation requirements of the external prevention and control linkage device.

[0017] Specifically, the process of constructing the hierarchical alarm strategy is as follows: based on the fire feature detection parameters covered by the detectors, and combined with the early warning and fire alarm handling requirements of fire prevention and control, two alarm levels are divided and corresponding triggering logic is set. The first-level alarm is triggered when a single fire feature detection parameter reaches a preset threshold, and is defined as an early warning state. The second-level alarm is triggered when the temperature parameter and other fire feature detection parameters reach a preset threshold in conjunction, and is defined as a fire alarm state. Based on the two alarm levels, exclusive alarm status identifiers and signal output rules are defined.

[0018] Specifically, the process of outputting the early warning signal and the active drive signal is as follows: taking the detection judgment signal corresponding to the standardized detection data of fire characteristics as the core basis, outputting corresponding signals according to the hierarchical alarm strategy for different scenarios; when a single standardized detection data reaches the preset standard, a level one alarm detection judgment signal is generated, and the early warning signal is generated and output simultaneously; when the standardized detection data corresponding to temperature and other standardized detection data reach the preset standard in synergy, a level two alarm detection judgment signal is generated, the early warning signal is generated and output simultaneously, and the active drive signal is generated based on the preset output specification.

[0019] Specifically, a composite fire detector testing experimental host includes: a sensor signal acquisition module, a signal processing and standardization generation module, a threshold matching module, and a graded alarm module; The sensing signal acquisition module acquires the optical signal caused by smoke particles, acquires the resistance fluctuation signal based on the correlation between temperature and sensing characteristics, and acquires the current signal through the electrochemical, catalytic combustion and semiconductor reaction between combustible gas and sensing material. The signal processing and standardization generation module amplifies and optimizes the current signal, reduces noise in the optical signal and the resistance fluctuation signal, integrates them to generate an initial analog signal, and normalizes the initial analog signal into a digital signal of a unified format through circuit adaptation and conversion. At the same time, the digital signal is converted into quantized values ​​of feature parameters, and standardized detection data is generated by adopting a data standardization optimization mechanism. The threshold matching module constructs a multi-parameter threshold matching model, compares the standardized detection data with a preset threshold, outputs the matching result, generates a corresponding detection judgment signal, outputs the detection judgment signal through a bus communication mechanism, and synchronously generates a linkage signal that can trigger subsequent alarm actions. The graded alarm module constructs a graded alarm strategy based on the detection and judgment signal and the linkage signal, and outputs early warning signal and active drive signal.

[0020] The beneficial effects of this invention are as follows: It enables the synchronous acquisition and targeted processing of multiple types of sensor signals. It designs an optimized logic for graded amplification and interference suppression for combustible gas current signals. It also designs a dedicated noise reduction strategy based on the inherent interference characteristics of smoke optical signals and temperature resistance fluctuation signals. This effectively reduces signal distortion and noise interference, fully extracts effective feature information from the signals, improves the accuracy of subsequent signal quantization and conversion, and ensures the reliability of signal processing in detection experiments.

[0021] A standardized signal conversion and data processing system is constructed. Through the conversion of digital signals in a unified format, the quantitative conversion of matching detection principles, and the standardized optimization mechanism including calibration correction and anomaly screening, the differences in format and measurement of different sensor signals are eliminated, system errors are offset, distorted and abnormal data are removed, and the accuracy, comparability and authority of detection data are improved, providing accurate data support for subsequent parameter determination.

[0022] The design incorporates a scientifically sound multi-parameter threshold matching model that integrates independent comparison of single parameters with collaborative comparison of temperature and other parameters. It also supports dynamic adjustment of thresholds based on application scenarios, aligning with the collaborative change patterns of multiple parameters during fire development. This effectively reduces misjudgments and omissions in detection experiments, enhancing the rationality and adaptability of parameter determination for composite fire detectors.

[0023] Establish a graded alarm strategy that aligns with fire prevention and control needs, clearly distinguish between early warning states based on single parameter anomalies and fire alarm states based on multi-parameter coordinated anomalies, and synchronously generate standardized linkage signals. This will not only achieve graded and accurate alarms for fire detection but also effectively adapt to external fire prevention and control linkage devices, ensuring the timely triggering of subsequent alarm linkage actions and enhancing the practical application value of detection experiments.

[0024] This integrated module combines sensor signal acquisition, signal processing and standardization generation, threshold matching, and graded alarm functions, enabling efficient connection between each stage. It can adapt to the testing needs of composite fire detectors of different specifications, and takes into account both factory batch testing and on-site calibration and debugging application scenarios. It significantly improves the overall efficiency of composite fire detector testing experiments and promotes the standardization and precision development of composite detector testing technology in the field of fire protection testing. Attached Figure Description

[0025] To facilitate understanding by those skilled in the art, the present invention will be further described below with reference to the accompanying drawings.

[0026] Figure 1 This is a flowchart illustrating the testing host and testing method of a composite fire detector according to the present invention. Figure 2 This is a structural block diagram of a composite fire detector testing experimental host and its testing method according to the present invention. Detailed Implementation

[0027] To further illustrate the technical means and effects of the present invention in achieving its intended purpose, the following detailed description of the specific implementation methods, structures, features, and effects of the present invention, in conjunction with the accompanying drawings and preferred embodiments, is provided.

[0028] Please see Figure 1-2 A composite fire detector testing experimental host and its testing method, comprising: S1: Obtain the optical signal triggered by smoke particles, obtain the resistance fluctuation signal based on the correlation between temperature and sensing characteristics, and obtain the current signal through the electrochemical, catalytic combustion and semiconductor reaction between combustible gas and sensing material. S2: The current signal is amplified and optimized, the optical signal and the resistance fluctuation signal are denoised, and an initial analog signal is generated. The initial analog signal is normalized into a digital signal of a unified format through circuit adaptation and conversion. At the same time, the digital signal is converted into the quantized value of the feature parameter. A data standardization optimization mechanism is adopted to generate standardized detection data. S3: Construct a multi-parameter threshold matching model, compare the standardized detection data with the preset threshold, output the matching result, generate the corresponding detection judgment signal, output the detection judgment signal through the bus communication mechanism, and synchronously generate a linkage signal that can trigger subsequent alarm actions. S4: Based on the detection and judgment signal and the linkage signal, construct a hierarchical alarm strategy and output early warning signal and active drive signal.

[0029] Specifically, the process of amplifying and optimizing the current signal is as follows: first, the source characteristics of the current signal are identified, a hierarchical amplification logic is adopted, the amplification gain is dynamically adjusted according to the amplitude difference of the current signal generated by the reaction of combustible gas, an interference suppression mechanism is integrated during the amplification process, environmental factors and noise interference introduced by the signal transmission link are filtered out, and the amplified current signal is converted into a stable electrical signal form required for subsequent quantization through signal form adaptation processing.

[0030] Specifically, the noise reduction process for the optical signal and the resistance fluctuation signal is as follows: First, distinguish the interference differences between the optical signal and the resistance fluctuation signal; based on the optical signal, reduce the intrusion of ambient stray light by utilizing the light-shielding protection effect of the closed detection structure, and then perform filtering to filter out noise that exceeds the effective signal range; based on the resistance fluctuation signal, based on the inherent correlation between temperature and resistance, extract the effective fluctuation that corresponds to temperature changes through characteristic correlation filtering logic, and eliminate disordered interference signals without temperature correlation; and then perform smoothing processing on the optical signal and the resistance fluctuation signal respectively.

[0031] Specifically, the process of integrating and generating the initial analog signal is as follows: classifying and identifying the processed optical signal, the resistance fluctuation signal, and the current signal; eliminating signal format differences through a signal adaptation link; and then using the logic of classification, aggregation, and synchronous integration to perform collaborative aggregation and generate the initial analog signal.

[0032] Specifically, the process of normalizing the initial analog signal into a unified digital signal through circuit adaptation and conversion is as follows: First, the characteristic differences of the optical signal, the resistance fluctuation signal, and the current signal are identified, and the parameter adaptability of the signals is adjusted through the adaptation link to eliminate the inherent differences of the initial analog signal; then, signal discretization conversion logic is used to convert the parameter-adjusted initial analog signal into a discretized digital form; the format of the discretized digital signal is normalized to unify the signal transmission specifications, data structure, and parameter type identification; and the distorted signal in the conversion process is eliminated through signal validity verification.

[0033] Specifically, the process of converting the digital signal into a quantized value of the feature parameter is as follows: first, identify the fire feature parameter type corresponding to the digital signal, match the characteristic correlation law corresponding to the detection principle, and convert it according to the preset signal-parameter correspondence benchmark to generate the quantized value of the feature parameter.

[0034] Specifically, the data standardization and optimization mechanism includes: calibrating and correcting the quantized values ​​of the feature parameters based on the detection principle and signal characteristics of the feature parameters to offset system errors; uniformly adapting the quantized values ​​corresponding to smoke concentration, temperature, and combustible gas concentration to the metrological specifications for subsequent processing to eliminate differences in the original measurement methods of the parameters; standardizing the data structure and transmission format of the quantized values; and simultaneously filtering out abnormal and distorted data based on the reasonable variation range and inherent laws of the feature parameters to generate the standardized detection data.

[0035] In this embodiment, based on the V3000-BG-Test composite detector testing host and its matching test chamber, and specifically for the V325-PTCHV five-in-one composite detector (detecting smoke, temperature, CO, H2, and VOC), the implementation is as follows: Acquisition of multiple types of sensor signals: Utilizing the enclosed detection structure, optical labyrinth, and multi-principle sensing components of the test chamber, three types of core signals are simultaneously collected, with each signal directly correlated to corresponding fire characteristic parameters: Smoke optical signal (A): After smoke particles enter the optical maze, the light emitted by the infrared emitter is diffusely reflected by the particles, captured by the photodetector and converted into a voltage signal A. The signal amplitude increases with the increase of smoke concentration. Temperature resistance fluctuation signal (B): Temperature changes are sensed by an NTC thermistor sensor. Temperature fluctuations cause regular changes in the sensor's resistance, which are then converted into a signal B that is synchronized with the temperature change. The resistance and temperature are inversely correlated, and the fluctuation amplitude reflects the degree of temperature change. Combustible gas current signals: CO undergoes an oxidation-reduction reaction with the electrochemical sensor, generating a weak current signal (C); H2 undergoes flameless combustion on the surface of the catalytic combustion sensor under the action of a catalyst, causing the bridge to become unbalanced and output a current signal (D); VOC undergoes a chemical reaction with the semiconductor gas-sensitive layer, causing a change in resistance and converting it into a current signal (E). The amplitudes of signals C, D, and E are all positively correlated with the concentration of the corresponding gas.

[0036] Signal processing and standardized detection data generation: Current signal amplification optimization: First, the signal identification module distinguishes the amplitude differences of C, D, and E. Then, the operational amplifier gain is dynamically adjusted using a graded amplification logic—high gain amplification is used for signals with weak amplitudes, and adaptive gain amplification is used for signals with relatively stable amplitudes. During the amplification process, a filtering interference suppression mechanism is integrated to filter out noise introduced by power supply noise and environmental interference. Then, the waveform distortion is corrected by the signal shaping circuit, and finally, it is converted into a stable amplified voltage signal (C1, D1, E1) to ensure that the signal amplitude is adapted to the subsequent processing requirements.

[0037] Optical signal and resistance fluctuation signal noise reduction: Signal A noise reduction: The closed light-shielding structure of the optical labyrinth of the test chamber is used to reduce the intrusion of external stray light; then, a low-pass filter circuit is used to set the cutoff frequency that is suitable for the effective signal to filter high-frequency noise; finally, a moving average smoothing algorithm is used to continuously process the filtered signal to eliminate random fluctuations and obtain a stable preprocessed signal (A1).

[0038] Signal B noise reduction: Based on the inherent correlation between temperature and resistance of NTC sensor, a feature correlation screening logic is constructed, a correlation threshold range is set, and effective fluctuations corresponding to temperature changes are extracted through trend analysis to eliminate disordered interference signals without temperature correlation; then, after smoothing algorithm processing, residual small fluctuations are eliminated to generate a stable preprocessed signal (B1).

[0039] Initial analog signal integration: Classification Identification: The signal processing module adds unique parameter type identifiers (smoke, temperature, CO, H2, VOC) and millisecond-level timestamps to A1, B1, C1, D1, and E1 respectively to ensure that each signal is traceable and free from confusion; Format adaptation: Through the signal adaptation link (L), the amplitude range and output impedance of the five types of signals are uniformly adjusted to the preset adaptation range, eliminating the inherent format differences of different types of signals and ensuring the compatibility of transmission and integration. Collaborative aggregation: Using classification and synchronous integration logic, the five types of adaptive signals are time-aligned based on timestamps to keep the error within a very small range. Then, they are collaboratively aggregated in order of parameter type to generate an initial set of analog signals (F) containing all the original information. Multi-path parallel transmission is used to avoid signal delay or loss.

[0040] Unified format digital signal conversion: Parameter adaptation: By analyzing the differences in amplitude range, rate of change, etc. of various signals in set F through the signal characteristic identification unit, and further adjusting parameters such as sampling triggering conditions and transmission bandwidth with the help of link L, the inherent differences caused by different detection principles are eliminated, and a parameter-unified adapted analog signal (G) is obtained. Discretization conversion: A high-precision ADC conversion module is used. Based on signal discretization logic, a sampling frequency that adapts to the rate of signal change is set to convert various analog signals in signal G into discrete digital signals, which correspond to G1 (smoke), G2 (temperature), G3 (CO), G4 (H2), and G5 (VOC), respectively. Standardized format: In accordance with the RS485 communication protocol and host processing specifications, the transmission baud rate, data bits, parity bits, stop bits, and other specifications of digital signals are standardized; the data structure (including parameter identifiers, data values, and check codes) is standardized; and the parameter type encoding rules are unified to generate a set of digital signals (H) with a completely uniform format. Validity verification: A dual verification logic is constructed. The first layer performs a reasonable value range verification (removing invalid values ​​that are outside the normal range of the signal). The second layer performs a trend consistency verification (removing distorted signals that suddenly change in continuous sampling points). At the same time, the integrity of the data is verified through redundancy verification, and finally the valid digital signal (I) is retained.

[0041] Feature parameter quantization conversion: Signal-parameter matching: The parameter identification unit analyzes the parameter identifier of signal I to determine its corresponding fire characteristic parameter type (smoke concentration, temperature, CO concentration, H2 concentration, VOC concentration). Correlation rule matching: For different parameter types, match the characteristic correlation rules corresponding to their detection principles -- smoke concentration matches the "light reflection amplitude-concentration" correlation rule, temperature matches the "resistance-temperature" conversion rule, CO concentration matches the "electrochemical reaction current-concentration" correlation rule, H2 concentration matches the "catalytic combustion-concentration" correlation rule, and VOC concentration matches the "semiconductor resistance change-concentration" correlation rule. Quantization conversion: The preset signal-parameter correspondence reference database (K) is called. This database contains the calibration correlation between the signal values ​​of each parameter and the quantization value. The interpolation algorithm is used to accurately convert each effective digital signal and generate the quantization values ​​of the characteristic parameters: Q1 (smoke concentration), Q2 (temperature), Q3 (CO concentration), Q4 (H2 concentration), and Q5 (VOC concentration), ensuring that the conversion error is controlled within a reasonable range.

[0042] Standardized test data generation: Based on a data standardization and optimization mechanism, Q1-Q5 are processed in multiple dimensions to ensure data accuracy, consistency, and effectiveness. Calibration correction: Based on the detection principle and signal characteristics of each parameter, the preset system error calibration coefficient (M) is called, and the system error caused by sensor drift, circuit noise, etc. is offset by linear correction logic to obtain the calibrated quantized value; Metrological standardization: The various quantified values ​​after calibration (different parameters were originally measured in different ways) are uniformly adapted to the metrological specifications of the host computer for subsequent processing, eliminating metrological differences and ensuring that the data can be directly compared and analyzed collaboratively; Standardized format: In accordance with the host data storage and transmission requirements, the data structure (consistent field type and length) and transmission format (consistent encoding method and byte order) of the quantified values ​​are standardized to ensure compatible transmission between modules; Anomaly screening: Based on the reasonable range of change and inherent change patterns of each parameter, anomaly detection algorithms are used to identify and remove distorted data that exceeds the reasonable range or has abnormal change trends; Final generation: After the above calibration, unification, standardization and screening processes, standardized detection data (S) containing all valid feature parameter information is generated. This data can be directly used for subsequent threshold matching, alarm judgment and communication with external devices, providing accurate and reliable support for the performance testing of composite detectors.

[0043] Specifically, the process of constructing the multi-parameter threshold matching model is as follows: based on the standardized detection data, a corresponding threshold is set, and the threshold is dynamically adjusted according to the differences in application scenarios; a core matching logic is constructed, namely single-parameter threshold matching, which compares the standardized detection data with the corresponding preset threshold to determine the compliance status of a single parameter; composite-parameter threshold matching, which associates the temperature parameter with other feature parameters to determine the overall compliance status; and data validity verification logic is used to eliminate abnormal and distorted data.

[0044] Specifically, the process of generating the corresponding detection and judgment signal is as follows: based on the matching result, the received matching result is parsed for type, and then the corresponding alarm logic and normal monitoring status are associated according to the parsed result type. For the alarm-type detection and judgment signal to be generated, key identification information is embedded. The single parameter type identifier and the first-level alarm attribute identifier are added to the first-level alarm signal, and the parameter type identifier and the second-level alarm attribute identifier are added to the second-level alarm signal. The generated detection and judgment signal is structurally optimized according to the transmission specification, and the signal transmission format, data encoding and identification rules are unified to generate the detection and judgment signal.

[0045] Specifically, the process of synchronously generating the linkage signal that can trigger subsequent alarm actions is as follows: the alarm attributes of the detection and judgment signal are analyzed, the secondary alarm signal is identified, and the linkage signal is generated according to the preset linkage signal output specifications and in combination with the activation requirements of the external prevention and control linkage device.

[0046] In this embodiment, based on standardized detection data (S), combined with the two-level alarm logic of the V325-PTCHV detector and the communication and linkage characteristics of the V3000-BG-Test host, multi-parameter threshold matching, detection judgment signal generation, and linkage signal output are completed. The specific implementation is as follows: Construct a multi-parameter threshold matching model: Preset Threshold Setting and Dynamic Adjustment: For the five characteristic parameters (smoke concentration Q1, temperature Q2, CO concentration Q3, H2 concentration Q4, VOC concentration Q5) included in the standardized detection data S, corresponding preset thresholds (T1-T5) are set respectively. The threshold benchmarks refer to the detector's factory calibration standards (such as smoke concentration alarm threshold, temperature alarm threshold, etc.). Simultaneously, a dynamic threshold adjustment module (X) is equipped, which allows for flexible modification of the values ​​of T1-T5 based on environmental differences in application scenarios (such as energy storage containers, battery packs, etc.) via adjustment commands input through the main unit's keypad, adapting the thresholds to the fire prevention and control needs of different scenarios.

[0047] Core matching logic execution: Single parameter threshold matching: Q1-Q5 in S are compared one by one with the corresponding preset thresholds T1-T5 to determine the compliance status of a single parameter. When the quantized value of a parameter reaches or exceeds the corresponding threshold, the parameter is determined to be in "compliance alarm state"; if the threshold is not reached, it is determined to be in "normal state".

[0048] Composite parameter threshold matching: Based on the coordinated change pattern of temperature and other parameters during fire development, a temperature correlation matching logic is constructed, and temperature parameter Q2 is correlated and compared with Q1, Q3, Q4, and Q5 respectively. When Q2 reaches T2 (temperature threshold), and any other parameter reaches its corresponding threshold, it is determined to be a "coordinated compliance alarm state"; if only Q2 meets the standard or only one other single parameter meets the standard, the coordinated compliance judgment is not triggered.

[0049] Data validity verification: Reuse the anomaly detection logic from the previous data standardization process to perform a second verification on the S data participating in threshold matching, and remove abnormal and distorted data caused by sudden environmental interference or instantaneous sensor drift to ensure that threshold comparison is based only on valid data and avoid misjudgment.

[0050] Generate corresponding detection and judgment signals: Matching result type analysis: The threshold matching results are classified and identified by the signal analysis module (Y), and three types of results are distinguished: First, single parameter compliance alarm (only one of Q1-Q5 meets the standard); second, coordinated compliance alarm (Q2 meets the standard and any other parameter meets the standard); third, all parameters fail to meet the standard (normal monitoring state).

[0051] Detection and Judgment Signal Generation and Identifier Embedding: Normal monitoring signal (J3): When all parameters fail to meet the standards, a normal status signal J3 is generated, which embeds the "normal attribute identifier" and real-time status information of each parameter, and provides feedback that the detector has no alarm and is operating normally.

[0052] Level 1 alarm signal (J1): When a single parameter meets the alarm standard, a Level 1 alarm signal J1 is generated, embedding the "Level 1 alarm attribute identifier" and the type identifier of the met parameter (such as smoke, CO, etc.) to clarify the alarm trigger source.

[0053] Level 2 alarm signal (J2): When a coordinated compliance alarm is detected, a level 2 alarm signal J2 is generated, which embeds the "level 2 alarm attribute identifier" and the parameter combination identifier of coordinated compliance (such as temperature + smoke, temperature + VOC, etc.) to indicate the triggering of the composite alarm logic.

[0054] Signal format unification and optimization: In accordance with the RS485 bus communication protocol specification, the structure of J1, J2, and J3 is optimized -- unifying the signal transmission format (including parameter identification segment, alarm attribute segment, and verification segment), data encoding method (ASCII encoding), and identification rules (consistent with the parameter type identification mentioned above), ensuring that the signal can be accurately identified and parsed by the host controller and external devices, generating a standardized set of detection and judgment signals (J).

[0055] Synchronous generation of linkage signals: Alarm attribute analysis: The alarm attribute analysis of the detection and judgment signal set (J) is performed by the linkage signal triggering module (Z) to accurately identify the secondary alarm signal (J2) -- the linkage signal generation process is started only when J2 is generated; when J1 and J3 are triggered, no linkage signal is generated, only status information is fed back.

[0056] Linkage signal specification adaptation: Based on the preset linkage signal output specification (refer to the detector OUT port output standard), combined with the start-up requirements of external control linkage devices (such as spraying equipment, sub-control valves), the linkage signal is set to a 24V active output signal (L). The signal output parameters (such as voltage amplitude and duration) are adapted to the start-up threshold of the external device to ensure that the signal can directly trigger the device to act.

[0057] Synchronous signal output: The detection and judgment signals (J1 / J2 / J3) are uploaded to the host controller via the RS485 communication board and displayed in real time on the display screen (green background and black text for normal status, red background and black text for alarm status); at the same time, the linkage signal (L) is output through the wiring harness plug-in terminal block of the host control box and sent synchronously to the external prevention and control linkage device, realizing the seamless connection of "alarm judgment - signal feedback - linkage start" and ensuring the timely triggering of fire prevention and control actions.

[0058] Specifically, the process of constructing the hierarchical alarm strategy is as follows: based on the fire feature detection parameters covered by the detectors, and combined with the early warning and fire alarm handling requirements of fire prevention and control, two alarm levels are divided and corresponding triggering logic is set. The first-level alarm is triggered when a single fire feature detection parameter reaches a preset threshold, and is defined as an early warning state. The second-level alarm is triggered when the temperature parameter and other fire feature detection parameters reach a preset threshold in conjunction, and is defined as a fire alarm state. Based on the two alarm levels, exclusive alarm status identifiers and signal output rules are defined.

[0059] Specifically, the process of outputting the early warning signal and the active drive signal is as follows: taking the detection judgment signal corresponding to the standardized detection data of fire characteristics as the core basis, outputting corresponding signals according to the hierarchical alarm strategy for different scenarios; when a single standardized detection data reaches the preset standard, a level one alarm detection judgment signal is generated, and the early warning signal is generated and output simultaneously; when the standardized detection data corresponding to temperature and other standardized detection data reach the preset standard in synergy, a level two alarm detection judgment signal is generated, the early warning signal is generated and output simultaneously, and the active drive signal is generated based on the preset output specification.

[0060] Specifically, a composite fire detector testing experimental host includes: a sensor signal acquisition module, a signal processing and standardization generation module, a threshold matching module, and a graded alarm module; The sensing signal acquisition module acquires the optical signal caused by smoke particles, acquires the resistance fluctuation signal based on the correlation between temperature and sensing characteristics, and acquires the current signal through the electrochemical, catalytic combustion and semiconductor reaction between combustible gas and sensing material. The signal processing and standardization generation module amplifies and optimizes the current signal, reduces noise in the optical signal and the resistance fluctuation signal, integrates them to generate an initial analog signal, and normalizes the initial analog signal into a digital signal of a unified format through circuit adaptation and conversion. At the same time, the digital signal is converted into quantized values ​​of feature parameters, and standardized detection data is generated by adopting a data standardization optimization mechanism. The threshold matching module constructs a multi-parameter threshold matching model, compares the standardized detection data with a preset threshold, outputs the matching result, generates a corresponding detection judgment signal, outputs the detection judgment signal through a bus communication mechanism, and synchronously generates a linkage signal that can trigger subsequent alarm actions. The graded alarm module constructs a graded alarm strategy based on the detection and judgment signal and the linkage signal, and outputs early warning signal and active drive signal.

[0061] In this embodiment, based on the detection judgment signal (J), linkage signal (L), and standardized detection data (S) generated in the previous embodiment, and combining the two-level alarm mechanism of the V325-PTCHV detector with the signal output characteristics of the V3000-BG-Test host, a hierarchical alarm strategy is constructed and the corresponding signals are accurately output. The specific implementation is as follows: Build a tiered alarm strategy: Two-level alarm levels and triggering logic definition: Based on the five fire characteristic parameters covered by the detectors (smoke concentration Q1, temperature Q2, CO concentration Q3, H2 concentration Q4, VOC concentration Q5), and combined with the tiered handling requirements of fire prevention and control from "early warning to fire alarm", the triggering boundaries of the two-level alarms are clearly defined: Level 1 alarm (early warning status): The triggering logic is bound to the single parameter threshold matching result mentioned above. That is, when any parameter (Q1 / Q3 / Q4 / Q5 / Q2 alone) in the standardized detection data S reaches the corresponding preset threshold (T1 / T2 / T3 / T4 / T5) and no other parameters meet the standard in coordination, the Level 1 alarm is triggered, which only indicates the potential fire risk and does not require the initiation of physical prevention and control actions.

[0062] Level 2 alarm (fire alarm status): The triggering logic is bound to the result of the composite parameter threshold matching. That is, when the temperature parameter Q2 reaches the threshold T2, and any one of the parameters Q1 / Q3 / Q4 / Q5 simultaneously reaches the corresponding threshold, the level 2 alarm is triggered, indicating that a fire has occurred or is about to spread, and emergency prevention and control actions need to be initiated.

[0063] Dedicated alarm status indicators and output rules: Status Identification Specification: Dedicated visual and signal identifiers are set for two-level alarms, adapting to the hardware display characteristics of detectors and hosts. When a level 1 alarm occurs, the red LED indicator on the detector flashes, and the corresponding parameter area on the host display shows red text on a black background, embedding the "early warning attribute identifier". When a level 2 alarm occurs, the red LED indicator on the detector remains on, and the corresponding parameter combination area on the host display shows red text on a black background, embedding the "fire alarm attribute identifier". At the same time, the corresponding indicator on the test circuit board of the test chamber remains on (indicating active output is valid).

[0064] Signal output rules: Level 1 alarm only outputs communication signals and no physical drive signals; Level 2 alarm outputs both communication signals and physical drive signals simultaneously, and the signal output timing is "communication signals take priority, drive signals have minimal delay and are synchronized", ensuring seamless connection between status feedback and prevention and control actions.

[0065] Output warning signals and active drive signals: Scenario 1: Level 1 Alarm (Early Warning Status) Signal Output Triggering condition: When a single parameter in the standardized detection data S (such as Q1 smoke concentration, Q3 CO concentration, etc.) reaches a preset threshold, a first-level alarm detection judgment signal J1 is generated.

[0066] Signal generation and output: Based on J1, a warning signal (Y) is generated according to the hierarchical alarm strategy. The warning signal Y adopts the RS485 communication protocol format, embedding the "warning attribute identifier" and trigger parameter type identifier (such as "smoke-warning" and "CO-warning"). It is uploaded to the controller through the host RS485 communication board and synchronously transmitted to the communication interface of the detector.

[0067] Status feedback: The red LED indicator on the detector flashes, and the parameter area of ​​the corresponding address on the host display shows red text on a black background, refreshing the quantified value of the parameter in real time to remind the operator to pay attention to potential risks; at this time, there is no voltage output at the detector's OUT port, and external control devices (such as spraying equipment and sub-control valves) remain in standby mode.

[0068] Scenario 2: Level 2 Alarm (Fire Alarm Status) Signal Output Triggering condition: Temperature parameter Q2 in the standardized detection data S reaches the threshold T2, and any other parameter (such as Q1+Q2, Q4+Q2, etc.) simultaneously meets the standard, generating a secondary alarm detection judgment signal J2.

[0069] Synchronous output of early warning signals: Using the early warning signal generation logic of Scenario 1, an early warning signal Y containing "fire alarm attribute identifier" and collaborative parameter combination identifier (such as "temperature + smoke - fire alarm") is generated and synchronously output to the host and related linkage devices through RS485 bus to realize rapid notification of fire alarm status.

[0070] Active drive signal generation and output: Based on the preset OUT port output specification (refer to the detector terminal pin definition), an active drive signal (Q) is generated using J2 as the trigger command. This signal is a 24V DC voltage signal, which is output through the wiring harness plug-in terminal block of the host control box and the detector OUT+ and OUT- ports to adapt to the start-up voltage requirements of external control devices (such as spraying equipment and valve opening voltage of sub-control valves).

[0071] Status feedback: The red LED indicator of the detector is constantly lit, and the corresponding LED indicator of the detector on the test circuit board of the test chamber is synchronously lit (indicating that the active drive signal output is normal); the parameter combination area of ​​the corresponding address on the host display screen displays red text on a black background, while scrolling the message "Fire alarm triggered, linkage started", ensuring that the operator can intuitively grasp the fire alarm status and equipment linkage status.

[0072] Scenario 3: Normal Monitoring Status Signal Output. When all parameters in the standardized detection data S do not reach the preset threshold, a normal detection judgment signal J3 is generated. At this time, no warning signal or active drive signal is generated. The detector's green power indicator light remains constantly on, and the corresponding area on the main unit's display screen shows green text on a black background, indicating that the detector is in a stable monitoring state and there is no fire risk. The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or alterations to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the present invention. Any simple modifications, equivalent changes and alterations made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the scope of the present invention.

Claims

1. A composite fire detector testing experimental host and its testing method, characterized in that, include: S1: Obtain the optical signal triggered by smoke particles, obtain the resistance fluctuation signal based on the correlation between temperature and sensing characteristics, and obtain the current signal through the electrochemical, catalytic combustion and semiconductor reaction between combustible gas and sensing material. S2: The current signal is amplified and optimized, the optical signal and the resistance fluctuation signal are denoised, and an initial analog signal is generated. The initial analog signal is normalized into a digital signal of a unified format through circuit adaptation and conversion. At the same time, the digital signal is converted into the quantized value of the feature parameter. A data standardization optimization mechanism is adopted to generate standardized detection data. S3: Construct a multi-parameter threshold matching model, compare the standardized detection data with the preset threshold, output the matching result, generate the corresponding detection judgment signal, output the detection judgment signal through the bus communication mechanism, and synchronously generate a linkage signal that can trigger subsequent alarm actions. S4: Based on the detection and judgment signal and the linkage signal, construct a hierarchical alarm strategy and output early warning signal and active drive signal.

2. The method according to claim 1, characterized in that, The specific process of amplifying and optimizing the current signal is as follows: First, identify the source characteristics of the current signal, adopt hierarchical amplification logic, dynamically adjust the amplification gain according to the amplitude difference of the current signal generated by the reaction of combustible gas, integrate the interference suppression mechanism during the amplification process, filter out noise interference introduced by environmental factors and signal transmission links, and convert the amplified current signal into a stable electrical signal form required for subsequent quantization through signal form adaptation processing.

3. The method according to claim 1, characterized in that, The specific process for noise reduction of the optical signal and the resistance fluctuation signal is as follows: first, distinguish the interference differences between the optical signal and the resistance fluctuation signal; based on the optical signal, reduce the intrusion of ambient stray light by means of the light-shielding protection of the closed detection structure, and then perform filtering to filter out noise that exceeds the effective signal range; Based on the resistance fluctuation signal and the inherent correlation between temperature and resistance, effective fluctuations that correspond to temperature changes are extracted through characteristic correlation filtering logic, while disordered interference signals without temperature correlation are eliminated; the optical signal and the resistance fluctuation signal are smoothed respectively.

4. The method according to claim 1, characterized in that, The specific process for integrating and generating the initial analog signal is as follows: classifying and identifying the processed optical signal, the resistance fluctuation signal, and the current signal; eliminating signal format differences through a signal adaptation link; and then using the logic of classification, aggregation, and synchronous integration to perform collaborative aggregation and generate the initial analog signal.

5. The method according to claim 1, characterized in that, The specific process of normalizing the initial analog signal into a digital signal of a uniform format through circuit adaptation conversion is as follows: first, identify the characteristic differences of the optical signal, the resistance fluctuation signal and the current signal, and adjust the parameter adaptability of the signal through the adaptation link to eliminate the inherent differences of the initial analog signal; Then, signal discretization conversion logic is used to convert the initial analog signal with adjusted parameters into a discretized digital form; the format of the discretized digital signal is standardized to unify the signal transmission specifications, data structure and parameter type identification; and distorted signals in the conversion process are eliminated through signal validity verification.

6. The method according to claim 1, characterized in that, The specific process of converting the digital signal into a feature parameter quantization value is as follows: first, identify the fire feature parameter type corresponding to the digital signal, match the characteristic correlation law corresponding to the detection principle, and convert it according to the preset signal-parameter correspondence benchmark to generate the feature parameter quantization value.

7. The method according to claim 1, characterized in that, The data standardization and optimization mechanism specifically includes: calibrating and correcting the quantized values ​​of the feature parameters based on the detection principle and signal characteristics of the feature parameters to offset system errors; uniformly adapting the quantized values ​​corresponding to smoke concentration, temperature, and combustible gas concentration to the metrological specifications for subsequent processing to eliminate differences in the original measurement methods of the parameters; standardizing the data structure and transmission format of the quantized values; and simultaneously filtering out abnormal and distorted data based on the reasonable variation range and inherent laws of the feature parameters to generate the standardized detection data.

8. The method according to claim 1, characterized in that, The specific process of constructing the multi-parameter threshold matching model is as follows: based on the standardized detection data, a corresponding threshold is set, and the threshold is dynamically adjusted according to the differences in application scenarios; the core matching logic is constructed, and single-parameter threshold matching is performed by comparing the standardized detection data with the corresponding preset threshold to determine the compliance status of a single parameter; Composite parameter threshold matching correlates temperature parameters with other feature parameters to determine the collaborative compliance status; at the same time, data validity verification logic eliminates abnormal and distorted data.

9. The method according to claim 1, characterized in that, The specific process for generating the corresponding detection and judgment signal is as follows: Based on the matching result, the received matching result is parsed for type, and then the corresponding alarm logic and normal monitoring status are associated according to the parsed result type. For the alarm-type detection and judgment signal to be generated, key identification information is embedded. The single parameter type identifier and the first-level alarm attribute identifier are added to the first-level alarm signal, and the parameter type identifier and the second-level alarm attribute identifier are added to the second-level alarm signal. The generated detection and judgment signal is structurally optimized according to the transmission specification, and the signal transmission format, data encoding and identification rules are unified to generate the detection and judgment signal.

10. The method according to claim 1, characterized in that, The specific process of synchronously generating the linkage signal that can trigger subsequent alarm actions is as follows: the alarm attributes of the detection and judgment signal are analyzed, the secondary alarm signal is identified, and the linkage signal is generated according to the preset linkage signal output specifications and in combination with the activation requirements of the external prevention and control linkage device.

11. The method according to claim 1, characterized in that, The specific process of constructing the hierarchical alarm strategy is as follows: Based on the fire feature detection parameters covered by the detectors, and combined with the early warning and fire alarm handling requirements of fire prevention and control, two alarm levels are divided and corresponding triggering logic is set. The first-level alarm is triggered when a single fire feature detection parameter reaches a preset threshold, and is defined as an early warning state. The second-level alarm is triggered when the temperature parameter and other fire feature detection parameters reach a preset threshold in conjunction, and is defined as a fire alarm state. Based on the two alarm levels, exclusive alarm status identifiers and signal output rules are defined.

12. The method according to claim 1, characterized in that, The specific process of outputting the early warning signal and the active drive signal is as follows: taking the detection judgment signal corresponding to the standardized detection data of fire characteristics as the core basis, outputting corresponding signals according to the hierarchical alarm strategy for different scenarios; when a single standardized detection data reaches the preset standard, a level one alarm detection judgment signal is generated, and the early warning signal is generated and output simultaneously; when the standardized detection data corresponding to temperature and other standardized detection data reach the preset standard in synergy, a level two alarm detection judgment signal is generated, and the early warning signal is generated and output simultaneously, and the active drive signal is generated based on the preset output specification.

13. A composite fire detector testing experimental host, used to implement the method as described in any one of claims 1-12, characterized in that, include: Sensor signal acquisition module, signal processing and standardization generation module, threshold matching module, and graded alarm module; The sensing signal acquisition module acquires the optical signal caused by smoke particles, acquires the resistance fluctuation signal based on the correlation between temperature and sensing characteristics, and acquires the current signal through the electrochemical, catalytic combustion and semiconductor reaction between combustible gas and sensing material. The signal processing and standardization generation module amplifies and optimizes the current signal, reduces noise in the optical signal and the resistance fluctuation signal, integrates them to generate an initial analog signal, and normalizes the initial analog signal into a digital signal of a unified format through circuit adaptation and conversion. At the same time, the digital signal is converted into quantized values ​​of feature parameters, and standardized detection data is generated by adopting a data standardization optimization mechanism. The threshold matching module constructs a multi-parameter threshold matching model, compares the standardized detection data with a preset threshold, outputs the matching result, generates a corresponding detection judgment signal, outputs the detection judgment signal through a bus communication mechanism, and synchronously generates a linkage signal that can trigger subsequent alarm actions. The graded alarm module constructs a graded alarm strategy based on the detection and judgment signal and the linkage signal, and outputs early warning signal and active drive signal.

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