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CN-121985007-A - Building emergency equipment reliability monitoring management system and method

CN121985007ACN 121985007 ACN121985007 ACN 121985007ACN-121985007-A

Abstract

The invention discloses a reliability monitoring management system and method for building emergency equipment, which belong to the field of building safety monitoring, wherein the system adopts a cloud-side-end three-layer architecture and comprises a data acquisition module, an edge processing module, a cloud analysis module, an early warning execution module and a feedback optimization module, wherein the cloud analysis module is a system core and comprises a layered Bayesian network module, a Markov random field module and a dynamic probability threshold module, the layered Bayesian network module builds a multi-layer network structure to analyze the relevance of equipment faults, the Markov random field module builds a dynamic mapping relation between environmental parameters and equipment states, the dynamic probability threshold module dynamically adjusts an early warning threshold based on a loss function, and the probability map model predicts a frame so as to realize early prediction, relevance analysis and self-adaptive early warning of equipment faults.

Inventors

  • FAN YIFENG

Assignees

  • 重庆长括科技有限公司

Dates

Publication Date
20260505
Application Date
20260210

Claims (10)

  1. 1. A building emergency equipment reliability monitoring management system, comprising: the data acquisition module is used for acquiring environmental parameter data and emergency equipment state data in the building; the edge processing module is in communication connection with the data acquisition module and is used for receiving the environment parameter data and the emergency equipment state data and preprocessing the environment parameter data and the emergency equipment state data; The cloud analysis module is in communication connection with the edge processing module and is used for receiving the preprocessed environment parameter data and the state data of emergency equipment, and the cloud analysis module comprises: The hierarchical Bayesian network module is used for constructing a multi-layer network structure to analyze the relevance of the equipment faults, wherein the multi-layer network structure comprises an environment layer, a component layer, an equipment layer and a regional layer, and a fault relevance analysis result is generated; The Markov random field module is used for constructing the building environment and the equipment state into a uniform Markov random field, establishing a dynamic mapping relation between the environment parameters and the equipment state and generating equipment state distribution; The dynamic probability threshold module is used for receiving the fault association analysis result and the equipment state distribution, constructing a multidimensional decision space, dynamically adjusting an early warning threshold based on a loss function and generating early warning information; the early warning execution module is in communication connection with the cloud analysis module and is used for receiving the early warning information and triggering corresponding early warning response according to the early warning information; and the feedback optimization module is in communication connection with the early warning execution module and the cloud analysis module and is used for receiving an early warning response result and optimizing and adjusting parameters of the layered Bayesian network module, the Markov random field module and the dynamic probability threshold module.
  2. 2. The building emergency equipment reliability monitoring management system of claim 1, wherein the data acquisition module comprises: the environment parameter sensing unit is used for acquiring temperature, humidity, smoke concentration and air pressure environment parameters in the building; The equipment state monitoring unit is used for collecting the pressure value, the electric quantity and the on-off state operation parameters of the emergency equipment; the position information acquisition unit is used for acquiring the position of the equipment and the position information of the personnel; the data acquisition gateway is in communication connection with the environment parameter sensing unit, the equipment state monitoring unit and the position information acquisition unit, and is used for receiving and integrating various acquired data and transmitting the integrated data to the edge processing module.
  3. 3. The building emergency equipment reliability monitoring management system of claim 1, wherein the edge processing module comprises: the data cleaning unit is used for detecting and filling the missing data, identifying and processing the abnormal data and carrying out noise filtering on the sensing signals; The feature extraction unit is in communication connection with the data cleaning unit and is used for extracting time domain features, frequency domain features and associated features from cleaned data; the data standardization unit is in communication connection with the feature extraction unit and is used for carrying out standardization processing on the extracted features; And the local caching unit is in communication connection with the data standardization unit and is used for temporarily storing the processed data under the condition of network interruption.
  4. 4. The building emergency equipment reliability monitoring management system of claim 1, wherein the hierarchical bayesian network module comprises: the network structure unit is used for constructing an initial network structure based on the domain knowledge and the historical data; The parameter learning unit is in communication connection with the network structure unit and is used for calculating the conditional probability among the network nodes according to the historical data; The reasoning execution unit is in communication connection with the network structure unit and the parameter learning unit and is used for receiving real-time data, executing forward propagation and backward propagation reasoning calculation and outputting the state probability distribution of each node; and the dynamic updating unit is in communication connection with the reasoning execution unit and is used for dynamically adjusting the network structure and parameters according to the new data and the feedback result.
  5. 5. The building emergency equipment reliability monitoring management system of claim 1, wherein the markov random field module comprises: The field structure unit is used for constructing the building environment and the equipment state into discrete grid nodes and determining the neighborhood relation between the nodes based on the physical distance and the functional association; the potential function unit is in communication connection with the field structure unit and is used for constructing a node potential function, an edge potential function and a higher-order potential function; the state reasoning unit is in communication connection with the potential function unit and is used for calculating a global energy function, searching the minimum energy state configuration and calculating the edge probability distribution of each node; and the association analysis unit is in communication connection with the state reasoning unit and is used for quantifying the degree of correlation between the states of the equipment, identifying equipment groups with similar state changes and constructing an equipment association map.
  6. 6. The building emergency equipment reliability monitoring management system of claim 1, wherein the dynamic probability threshold module comprises: The decision space unit is used for constructing a multidimensional decision space comprising a fault probability dimension, a risk influence dimension, a time urgency dimension and a resource availability dimension; The loss function unit is in communication connection with the decision space unit and is used for designing quantization methods of false alarm loss, missing alarm loss and delay loss; the threshold value adjusting unit is in communication connection with the loss function unit and is used for dynamically adjusting the early warning threshold value based on the importance of the equipment, the environmental condition, the time factor and the historical performance; And the decision executing unit is in communication connection with the threshold value adjusting unit and is used for comparing the currently calculated fault probability with a dynamic threshold value to generate a hierarchical early warning signal.
  7. 7. The building emergency equipment reliability monitoring management system of claim 1, wherein the early warning execution module comprises: The early warning information generation unit is used for generating early warning information comprising equipment identification, position, fault type and treatment suggestion according to the early warning signals; the early warning distribution unit is in communication connection with the early warning information generation unit and is used for sending the early warning information to the corresponding terminal according to the early warning level and the personnel role; the response tracking unit is in communication connection with the early warning distribution unit and is used for tracking the early warning processing state and recording the processing result; and the upgrading mechanism unit is in communication connection with the response tracking unit and is used for automatically upgrading the early warning level when the early warning is not responded.
  8. 8. The building emergency equipment reliability monitoring management system of claim 1, wherein the feedback optimization module comprises: The result verification unit is used for comparing the early warning information with the actual fault condition and evaluating the early warning accuracy; The parameter adjustment unit is in communication connection with the result verification unit and is used for generating a parameter adjustment scheme according to a verification result; the model optimizing unit is in communication connection with the parameter adjusting unit and is used for optimizing the layered Bayesian network module, the Markov random field module and the dynamic probability threshold module according to a parameter adjusting scheme; And the performance evaluation unit is in communication connection with the model optimization unit and is used for evaluating the overall performance of the system and generating an optimization effect report.
  9. 9. The building emergency equipment reliability monitoring management system of claim 1, further comprising: the visual display module is in communication connection with the cloud analysis module and the early warning execution module and is used for displaying equipment states, fault prediction and early warning information in a graphical mode; The user interaction module is in communication connection with the visual display module and is used for receiving query conditions and control instructions input by a user and feeding back corresponding results to the user; and the equipment control module is in communication connection with the user interaction module and the cloud analysis module and is used for remotely controlling the emergency equipment according to an analysis result or a user instruction.
  10. 10. A building emergency equipment reliability monitoring and management method, adopting the building emergency equipment reliability monitoring and management system as claimed in any one of claims 1-9, characterized by comprising the following steps: collecting environmental parameter data and emergency equipment state data in a building; preprocessing the environment parameter data and the emergency equipment state data to generate preprocessed environment parameter data and emergency equipment state data; Constructing a layered Bayesian network, wherein the layered Bayesian network comprises an environment layer, a component layer, a device layer and a region layer, and analyzing device fault relevance based on the preprocessed environment parameter data and the emergency device state data to generate a fault relevance analysis result; Establishing a Markov random field, constructing a building environment and equipment states into a uniform Markov random field, establishing a dynamic mapping relation between environment parameters and the equipment states, and generating equipment state distribution; Constructing a multidimensional decision space, dynamically adjusting an early warning threshold value by using a loss function based on the fault correlation analysis result and the equipment state distribution, and generating early warning information; Triggering corresponding early warning response according to the early warning information; and receiving an early warning response result, and optimally adjusting parameters of the layered Bayesian network, the Markov random field and the early warning threshold.

Description

Building emergency equipment reliability monitoring management system and method Technical Field The invention relates to the field of building safety monitoring, in particular to a system and a method for monitoring and managing reliability of building emergency equipment, which are used for carrying out intelligent monitoring, predictive analysis and active management on the emergency equipment in a building. Background With the increasing complexity of modern buildings, the variety and number of emergency devices within the building have increased, including fire protection devices, emergency lighting, emergency evacuation systems, and the like. The reliability of these devices is directly related to the life and property safety of the building user. At present, the management of building emergency equipment mainly depends on periodic inspection and maintenance, and has the following problems: firstly, the traditional periodic inspection method cannot discover the potential faults of the equipment in time, and is often discovered after the equipment is completely failed, so that the reliability requirement in an emergency state cannot be met. Second, the correlation between devices is ignored and the risk of system cascading failure cannot be identified. Again, the impact of environmental factors on device reliability lacks an effective monitoring and assessment mechanism. Finally, the early warning mechanism is too simple, the early warning mode of the fixed threshold value leads to high false alarm rate, and the reliability of the early warning system is reduced. In the prior art, for example, chinese patent application CN201810123456.7 discloses a building fire-fighting equipment monitoring system, which can collect equipment status data in real time and perform simple analysis. However, this system lacks predictive analysis capability and fails to pre-warn of potential faults in advance. Another technology, such as the chinese patent application with application number cn201920654321.X, discloses a fire-fighting equipment monitoring method based on the internet of things, which still adopts simple threshold judgment although remote monitoring is realized, and cannot adapt to complex environmental changes. Accordingly, there is a need for a system and method that can intelligently monitor, predictively analyze, and actively manage building emergency equipment to improve the reliability of the emergency equipment. Disclosure of Invention The invention aims to provide a system and a method for monitoring and managing reliability of building emergency equipment, which solve the problems in the prior art and realize the technical span from passive response to active prediction. The invention provides a reliability monitoring and management system for building emergency equipment, which comprises: the data acquisition module is used for acquiring environmental parameter data and emergency equipment state data in the building; the edge processing module is in communication connection with the data acquisition module and is used for receiving the environment parameter data and the emergency equipment state data and preprocessing the environment parameter data and the emergency equipment state data; The cloud analysis module is in communication connection with the edge processing module and is used for receiving the preprocessed environment parameter data and the state data of emergency equipment, and the cloud analysis module comprises: The hierarchical Bayesian network module is used for constructing a multi-layer network structure to analyze the relevance of the equipment faults, wherein the multi-layer network structure comprises an environment layer, a component layer, an equipment layer and a regional layer, and a fault relevance analysis result is generated; The Markov random field module is used for constructing the building environment and the equipment state into a uniform Markov random field, establishing a dynamic mapping relation between the environment parameters and the equipment state and generating equipment state distribution; The dynamic probability threshold module is used for receiving the fault association analysis result and the equipment state distribution, constructing a multidimensional decision space, dynamically adjusting an early warning threshold based on a loss function and generating early warning information; the early warning execution module is in communication connection with the cloud analysis module and is used for receiving the early warning information and triggering corresponding early warning response according to the early warning information; and the feedback optimization module is in communication connection with the early warning execution module and the cloud analysis module and is used for receiving an early warning response result and optimizing and adjusting parameters of the layered Bayesian network module, the Markov random field module and the dynamic proba