Intelligent building system rule conflict detection method based on statistical model test

Abstract

The invention relates to the technical field of intelligent buildings, and particularly discloses an intelligent building system rule conflict detection method based on statistical model inspection, which comprises the following steps: constructing an intelligent building system rule model based on a price timed automaton network, and utilizing a statistical model inspection technology to detect the intelligent building system rule conflict. Calculating the execution action accessibility of each rule defined by the intelligent building system rule model; and based on the execution action accessibility of each rule, judging whether the intelligent building system has rule cycle conflict, execution action conflict, space-time cross conflict, condition coverage conflict, system constraint conflict, trigger condition conflict, rule coverage conflict or execution result conflict. According to the method, the difficulty of rule modeling and conflict detection of the intelligent building system can be effectively reduced, and the reliability of the intelligent building system is improved.

Description

Technical Field

[0001] The invention relates to the technical field of intelligent buildings, and in particular to an intelligent building system rule conflict detection method based on statistical model verification. Background Art

[0002] Traditional building intelligent systems write system business processes and equipment measurement and control logic directly into the application code. When the business logic is complex and changes, the modification and expansion of the system requires a lot of cost. Obviously, this highly coupled approach has been difficult to adapt to the rapid construction and development of the business logic of building intelligent systems. The rule engine extracts complex business logic from specific program codes, supports users to customize the system business processes and equipment measurement and control logic in the form of low code, and reduces the cost of secondary development and operation and maintenance of the system. In order to reduce the difficulty of building intelligent system development and improve development efficiency, existing building intelligent systems are mostly developed using rule engines based on "IF-THEN" rules. However, with the increase in the complexity of system business logic, dynamic interactions between devices, devices and subsystems, and subsystems are becoming more and more frequent, and there are chain reactions between devices. It is very easy for different rules to have conflicts such as action conflicts, time and space conflicts, rule coverage, and rule redundancy, which can easily lead to equipment misoperation and equipment failure, energy waste, and even threaten personal safety. How to eliminate rule conflicts before online execution through rule conflict detection and analysis verification and improve the reliability of building intelligent systems based on rule engines has become an urgent problem to be solved. Summary of the invention

[0003] In order to solve the above technical problems, the present invention provides a method for detecting rule conflicts in an intelligent building system based on statistical model verification.

[0004] In a first aspect, the present invention provides a method for detecting rule conflicts in an intelligent building system based on statistical model verification. The technical solution of the method is as follows:

[0005] Step 1: Based on the price-time automaton network, a rule model of the intelligent building system is constructed, and the execution action reachability of each rule defined in the rule model of the intelligent building system is calculated by using statistical model checking technology;

[0006] Step 2: Based on the reachability of the execution action of each rule, determine whether the intelligent building system has rule loop conflicts, execution action conflicts, time-space intersection conflicts, condition coverage conflicts, system constraint conflicts, trigger condition conflicts, rule coverage conflicts or execution result conflicts.

[0007] The beneficial effects of the intelligent building system rule conflict detection method based on statistical model verification of the present invention are as follows:

[0008] The method of the present invention can effectively reduce the difficulty of rule modeling and conflict detection of the intelligent building system, and improve the reliability of the intelligent building system.

[0009] On the basis of the above scheme, the intelligent building system rule conflict detection method based on statistical model verification of the present invention can also be improved as follows.

[0010] In an optional manner, the intelligent building system rule model is a five-tuple R:=<T,A,R,P,C> ;in:

[0011] T represents the triggering conditions of the rule, which include: system time, variable exceeding the limit, and device status change;

[0012] A represents the corresponding system operation (Actions) when the conditions are met. The system operation includes: equipment start and stop, parameter setting and subsystem linkage. A is represented by an assignment function;

[0013] R represents the rule action area (Region). The trigger condition T and system operation A during rule definition act on the global scope. When region R is set, the rule acts on the monitoring variables and device actions within this region.

[0014] P represents the priority of the rule. The default priority of a rule is 1 when it is defined. Users can modify the priority according to actual business needs and equipment measurement and control requirements. Rules with higher priorities are executed before rules with lower priorities.

[0015] C represents the constraints for rule execution. Under default conditions, no constraints are set for the rule. When the trigger condition T is met, the system operation A can be executed, that is, T→A. When the constraint C is set, the trigger condition T is met and the constraint is met at the same time, the system operation A can be executed, that is, T,C→A.

[0016] In an optional manner, the step of calculating the execution action reachability of each rule defined in the intelligent building system rule model by using the statistical model checking technology in step 1 includes:

[0017] The weighted metric temporal logic is adopted to determine the reachability expression of the rule execution action, and the rule execution action reachability expression and the intelligent building system rule model are loaded into the target statistical model verification tool to calculate the execution action reachability of each rule defined by the intelligent building system rule model.

[0018] In an optional manner, the rule execution action reachability expression is: Pr[<=Time](Ai), which represents the execution action reachability of the i-th rule execution action within the time of Time.

[0019] In an optional manner, the target statistical model verification tool is UPPAAL-SMC.

[0020] In an optional manner, step 2 includes:

[0021] Step 2-1: When the statistical model test result shows that Zeno behavior exists, if there are at least two rules that meet the preset conditions, it is determined that the intelligent building system has a rule cycle conflict; otherwise, it is determined that the intelligent building system does not have a rule cycle conflict;

[0022] Step 2-2: When the execution action reachability of any rule is less than 90%, judging whether the intelligent building system has execution action conflict, time-space intersection conflict or condition coverage conflict according to the rules containing the same action variables obtained by traversing all the rules;

[0023] Step 2-3: When the execution action reachability of any rule is greater than or equal to 90%, it is determined whether the intelligent building system has a system constraint conflict, a trigger condition conflict, a rule coverage conflict or an execution result conflict.

[0024] In an optional manner, step 2-1 further includes:

[0025] When the statistical model test results show that there is no Zeno behavior, it is determined whether the execution action reachability of any rule is less than 90%.

[0026] In an optional manner, the preset condition is: the execution action of the first rule of every two adjacent rules is equal to the triggering condition of the second rule, and the execution action of the last rule is equal to the triggering condition of the first rule.

[0027] In an optional manner, step 2-2 includes:

[0028] Step 2-2-1: When the execution action reachability of any rule is less than 90%, traverse the rules containing the same action variables in all rules to obtain at least one two-element set Dk{Rki, Rkj}; where Dk is the k-th two-element set, Rki is the i-th rule in the k-th two-element set, and Rkj is the j-th rule in the k-th two-element set;

[0029] Step 2-2-2: For the two rules Rki and Rkj in the two-element set Dk, then Tki∩ When Aki≠Akj, it is determined that there is an execution action conflict between Rki and Rkj, otherwise, it is determined that there is no execution action conflict between Rki and Rkj; wherein Tki is the trigger condition of the i-th rule in the k-th two-element set, Tkj is the trigger condition of the j-th rule in the k-th two-element set, Aki is the execution action of the i-th rule in the k-th two-element set, and Akj is the execution action of the j-th rule in the k-th two-element set;

[0030] Step 2-2-3: For the two rules Rki and Rkj in the two-element set Dk, when Tki(t)==True and Tkj(t)==True and Aki≠Akj, it is determined that there is a time-space crossover conflict between Rki and Rkj, otherwise, it is determined that there is no time-space crossover conflict between Rki and Rkj;

[0031] Step 2-2-4: For the two rules Rki and Rkj in the two-element set Dk, when Tki→Tkj or Tkj→Tki and Aki=Akj, it is determined that there is a conditional coverage conflict between Rki and Rkj; otherwise, it is determined that there is no conditional coverage conflict between Rki and Rkj.

[0032] In an optional manner, steps 2-3 include:

[0033] Step 2-3-1: Verify whether each rule whose execution action reachability is greater than or equal to 90% satisfies the corresponding constraint condition; if any rule does not satisfy the corresponding constraint condition, it is determined that there is a system constraint conflict in the intelligent building system; otherwise, it is determined that there is no system constraint conflict in the intelligent building system;

[0034] Step 2-3-2: Verify whether the reachability of the reverse action of each rule whose execution action reachability is greater than or equal to 90% is greater than 10%. If the reachability of the reverse action of any rule is greater than 10%, it is determined that there is a trigger condition conflict in the intelligent building system. Otherwise, it is determined that there is no trigger condition conflict in the intelligent building system.

[0035] Step 2-3-3: For the two rules Rki and Rkj in the two-element set Dk, when Tki==Tkj and When , it is determined that the intelligent building system has rule coverage conflicts; when all the two-element sets do not satisfy Tki==Tkj and It is determined that there is no rule coverage conflict in the intelligent building system;

[0036] Step 2-3-4: Use the statistical model verification tool UPPAAL-SMC to simulate the action variables in each rule Ai. If the action variables of any rule oscillate or the simulation is invalid, it is determined that there is an execution result conflict in the intelligent building system. If the action variables of all rules do not oscillate or the simulation is invalid, it is determined that there is no execution result conflict in the intelligent building system.

[0037] The above description is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention, it can be implemented according to the contents of the specification. In order to make the above and other purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] The accompanying drawings are only used to illustrate the embodiments and are not to be considered as limiting the present invention. In addition, the same reference symbols are used to represent the same components throughout the accompanying drawings. In the accompanying drawings:

[0039] Figure 1 A schematic flow chart of an embodiment of a method for detecting rule conflicts in an intelligent building system based on statistical model verification according to the present invention;

[0040] Figure 2 The schematic diagram is a formalized template of rule trigger source, rule, and rule responder based on the price time automaton network; Figure 2 (a) is a simple rule template, Figure 2 (b) is a rule template with time conditions. Figure 2 (c) is the rule trigger source Sensor template, Figure 2 (d) is the rule responder Actuator template;

[0041] Figure 3 A schematic diagram of the classification and meaning of various rule conflicts in intelligent building systems;

[0042] Figure 4 The following is an example diagram of the rule model and analysis results involved in rule cycle conflicts; Figure 4 (a) is an example of a rule loop conflict. Figure 4 (b) Zeno behavior occurs when rules conflict cyclically;

[0043] Figure 5 The rule model and analysis result example diagram for executing action conflicts; Figure 5 (a) is an example of the conflict of execution actions involved. Figure 5 (b) is the statistical model verification result when executing action conflicts;

[0044] Figure 6This is an example diagram of the rule model and analysis results involved in space-time cross-conflict, where: Figure 6 (a) is an example of the space-time cross-conflict involved. Figure 6 (b) is the statistical model test result when time-space cross-conflict occurs;

[0045] Figure 7 The following is an example diagram of the rule model and analysis results involved in conditional coverage conflicts, where: Figure 7 (a) is an example of a conditional coverage conflict. Figure 7 (b) Statistical model test results when condition coverage conflicts occur

[0046] Figure 8 This is an example diagram of the rule model and analysis results involved in the system constraint conflict, where: Figure 8 (a) is an example of a system constraint conflict. Figure 8 (b) is the statistical model test result when the system constraints conflict;

[0047] Fig. 9 The following is an example diagram of the rule model and analysis results involved in the trigger condition conflict, where: Fig. 9 (a) is an example of a trigger condition conflict. Fig. 9 (b) is the statistical model test result when the trigger conditions conflict;

[0048] Fig.10 The following is an example diagram of the rule model and analysis results involved in rule coverage conflicts, where: Fig.10 (a) is an example of a rule coverage conflict. Fig.10 (b) The statistical model verification results that occur when rule coverage conflicts;

[0049] Fig.11 This is an example diagram of the rule model and analysis results involved in the execution result conflict, where: Fig.11 (a) is an example of a conflicting execution result. Fig.11 (b) The statistical model test results that occur when the execution results conflict;

[0050] Fig.12 The present invention is an overall flow chart of a method for detecting rule conflicts in an intelligent building system based on statistical model verification. DETAILED DESCRIPTION

[0051] Exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present invention are shown in the drawings, it should be understood that the present invention can be implemented in various forms and should not be limited to the embodiments set forth herein.

[0052] Figure 1A flow chart of an embodiment of a method for detecting rule conflicts in an intelligent building system based on statistical model verification provided by the present invention is shown. The method for detecting rule conflicts in an intelligent building system based on statistical model verification can be executed by an electronic device such as a terminal device or a server. The terminal device can be any fixed or mobile terminal such as a user equipment (UE), a mobile device, a user terminal, a terminal, a cellular phone, a cordless phone, a personal digital assistant (PDA), a handheld device, a computing device, a vehicle-mounted device, a wearable device, etc. The server can be a single server or a server cluster composed of multiple servers. Any electronic device can implement the method for detecting rule conflicts in an intelligent building system based on statistical model verification by means of a processor calling computer-readable instructions stored in a memory. Figure 1 As shown, the following steps are included:

[0053] Step 1: Based on the price-time automaton network, construct an intelligent building system rule model, and use statistical model verification technology to calculate the execution action reachability of each rule defined in the intelligent building system rule model. Specifically:

[0054] 1) The rule model of intelligent building system is a five-tuple R:<T,A,R,P,C> ,like Figure 2 As shown in the figure, a formalized template of rule trigger source, rule, and rule responder is constructed based on the price-time automaton network; wherein:

[0055] T represents the triggering conditions (Triggers) of the rule, which include: system time, variable exceeding the limit and device status change; for example, temperature>28℃ means that the rule is triggered when the temperature is greater than 28℃, and t≥5min means that the rule is triggered after 5 minutes.

[0056] A represents the corresponding system operation (Actions) when the conditions are met. The system operation includes: equipment start and stop, parameter setting and subsystem linkage. A is represented by an assignment function. For example, actuator.Fan(shutOff) means shutting down the fan.

[0057] R represents the rule action area (Region). The trigger condition T and system operation A during rule definition act on the global scope. When region R is set, the rule acts on the monitoring variables and device actions within this region.

[0058] P represents the priority of the rule. The default priority of a rule is 1 when it is defined. Users can modify the priority according to actual business needs and equipment measurement and control requirements. Rules with higher priorities are executed before rules with lower priorities.

[0059] C represents the constraint conditions (Constraints) for rule execution. Under default conditions, no constraint conditions are set for the rule. When the trigger condition T is met, the system operation A can be executed, that is, T→A. When the constraint condition C is set, the trigger condition T is met, and the constraint conditions are met at the same time, the system operation A can be executed, that is, T, C→A. For example, rule R1 requires that windows be opened for ventilation when the carbon dioxide concentration is higher than 1000ppm and it is not raining outside, which can be described as outsideSensor.CO2()≥1000ppm→actuator.Window(open),constraints(weather≠rainy).

[0060] 2) The step of calculating the reachability of the execution action of each rule defined in the intelligent building system rule model by using statistical model checking technology comprises:

[0061] The weighted metric temporal logic is adopted to determine the reachability expression of the rule execution action, and the rule execution action reachability expression and the intelligent building system rule model are loaded into the target statistical model verification tool to calculate the execution action reachability of each rule defined by the intelligent building system rule model.

[0062] The reachability expression of rule execution action is: Pr[<=Time](Ai), which indicates the reachability of the execution action of the ith rule at the time of Time. The target statistical model verification tool is UPPAAL-SMC. The temporal logic expression in this embodiment is shown in Table 1 below.

[0063] Table 1: Commonly used temporal logic expressions and their meanings

[0064]

[0065] Step 2: Based on the reachability of the execution action of each rule, determine whether the intelligent building system has rule loop conflicts, execution action conflicts, time-space intersection conflicts, condition coverage conflicts, system constraint conflicts, trigger condition conflicts, rule coverage conflicts or execution result conflicts.

[0066] Among them, the classification and meaning of various rule conflicts are as follows Figure 3 Specifically, step 2 includes:

[0067] Step 2-1: When the statistical model test result shows the existence of Zeno behavior, if there are at least two rules that meet the preset conditions, it is determined that the intelligent building system has a rule cycle conflict; otherwise, it is determined that the intelligent building system does not have a rule cycle conflict.

[0068] Among them, Zeno behavior refers to event-triggered control, in which the control is triggered an infinite number of times within a finite time. The preset conditions are: the execution action of the previous rule in each of the two adjacent rules is equal to the triggering condition of the next rule, and the execution action of the last rule is equal to the triggering condition of the first rule. For example, if there are 2 or more rules in which the execution action (A1) of the first rule is equal to the triggering condition (T2) of the second rule, ..., the execution action (An) of the nth rule is equal to the triggering condition (T(n+1)) of the n+1th rule, and the execution action (A(n+1)) of the n+1th rule is equal to the triggering condition (T1) of the first rule, n≥1, then the intelligent building system has a rule cycle conflict (examples of rule models and analysis results involved in rule cycle conflicts are shown in Figure 4 As shown), otherwise, there is no rule cycle conflict in the intelligent building system.

[0069] It should be noted that when the statistical model test results show that there is no Zeno behavior, it is determined whether the execution action reachability of any rule is less than 90%.

[0070] Step 2-2: When the execution action accessibility of any rule is less than 90%, determine whether the intelligent building system has execution action conflict, time-space intersection conflict or condition coverage conflict based on the rules containing the same action variables traversed among all rules.

[0071] Specifically, step 2-2 includes:

[0072] Step 2-2-1: When the execution action reachability of any rule is less than 90%, traverse the rules containing the same action variables in all rules to obtain at least one two-element set Dk{Rki, Rkj}; where Dk is the kth two-element set, Rki is the i-th rule in the kth two-element set, and Rkj is the j-th rule in the kth two-element set.

[0073] Step 2-2-2: For the two rules Rki and Rkj in the two-element set Dk, immediately When Aki≠Akj, it is determined that there is an execution action conflict between Rki and Rkj (the rule model and analysis result examples involved in the execution action conflict are as follows Figure 5 As shown), otherwise, it is determined that there is no execution action conflict between Rki and Rkj; wherein Tki is the trigger condition of the i-th rule in the k-th two-element set, Tkj is the trigger condition of the j-th rule in the k-th two-element set, Aki is the execution action of the i-th rule in the k-th two-element set, and Akj is the execution action of the j-th rule in the k-th two-element set.

[0074] Step 2-2-3: For the two rules Rki and Rkj in the two-element set Dk, when Tki(t)==True and Tkj(t)==True and Aki≠Akj, it is determined that there is a time-space cross conflict between Rki and Rkj (the rule model and analysis results involved in the time-space cross conflict are shown in the following example) Figure 6 As shown), otherwise, it is determined that there is no time-space cross-conflict between Rki and Rkj.

[0075] Step 2-2-4: For the two rules Rki and Rkj in the two-element set Dk, when Tki→Tkj or Tkj→Tki and Aki=Akj, determine whether Rki and Rkj have a conditional coverage conflict (the rule model and analysis results involved in the conditional coverage conflict are shown in the example below) Figure 7 As shown), otherwise, it is determined that there is no conditional coverage conflict between Rki and Rkj.

[0076] Step 2-3: When the execution action reachability of any rule is greater than or equal to 90%, it is determined whether the intelligent building system has a system constraint conflict, a trigger condition conflict, a rule coverage conflict or an execution result conflict.

[0077] Specifically, steps 2-3 include:

[0078] Step 2-3-1: Verify whether each rule with execution action accessibility greater than or equal to 90% satisfies the corresponding constraint condition; if any rule does not satisfy the corresponding constraint condition, it is determined that the intelligent building system has a system constraint conflict; otherwise, it is determined that the intelligent building system does not have a system constraint conflict (the rule model and analysis result examples involved in the system constraint conflict are as follows Figure 8 shown).

[0079] Step 2-3-2: Verify whether the reachability of the reverse action of each rule whose execution action reachability is greater than or equal to 90% is greater than 10%. If the reachability of the reverse action of any rule is greater than 10%, it is determined that there is a trigger condition conflict in the intelligent building system. Otherwise, it is determined that there is no trigger condition conflict in the intelligent building system (the rule model and analysis result examples involved in the trigger condition conflict are as follows Fig. 9 shown).

[0080] Step 2-3-3: For the two rules Rki and Rkj in the two-element set Dk, when Tki==Tkj and When , it is determined that the intelligent building system has rule coverage conflicts; when all the two-element sets do not satisfy Tki==Tkj and It is determined that there is no rule coverage conflict in the intelligent building system (the rule model and analysis result examples involved in the rule coverage conflict are as follows Fig.10 shown).

[0081] Step 2-3-4: Use the statistical model checking tool UPPAAL-SMC to simulate the action variables in each rule Ai. If the action variables of any rule oscillate or the simulation is invalid, it is determined that there is an execution result conflict in the intelligent building system (the rule model and analysis result examples involved in the execution result conflict are as follows Fig.11 As shown), if the action variables of all rules do not show oscillation and simulation invalidity, it is determined that there is no execution result conflict in the intelligent building system.

[0082] The overall flow chart of this embodiment is as follows Fig.12 As shown, compared with the prior art, the technical solution of this embodiment has the following significant advantages: ① It can systematically and comprehensively detect and analyze the rule conflict problems existing in the intelligent building system; ② It supports simulation modeling of continuous environmental changes, and rule modeling and analysis are more in line with real engineering applications; ③ Rule analysis is implemented based on the existing visualization tool UPPAAL-SMC, with a friendly human-computer interface, which is easy for users to master and has high analysis and verification efficiency.

[0083] The technical solution of this embodiment can effectively reduce the difficulty of rule modeling and conflict detection of the intelligent building system, and improve the reliability of the intelligent building system.

[0084] In the description provided herein, a large number of specific details are described. However, it is understood that embodiments of the present invention can be practiced without these specific details. Similarly, in order to simplify the present invention and help understand one or more of the various inventive aspects, in the above description of exemplary embodiments of the present invention, the various features of the embodiments of the present invention are sometimes grouped together into a single embodiment, figure, or description thereof. Wherein, the claims that follow the specific embodiment are hereby expressly incorporated into the specific embodiment, wherein each claim itself is a separate embodiment of the present invention.

[0085] It should be noted that the above embodiments illustrate the present invention rather than limit it, and that those skilled in the art may devise alternative embodiments without departing from the scope of the appended claims. In the claims, any reference symbol between brackets shall not be construed as a limitation on the claims. The word "comprising" does not exclude the presence of elements or steps not listed in the claims. The word "one" or "an" preceding an element does not exclude the presence of a plurality of such elements. The present invention may be implemented by means of hardware comprising a number of different elements and by means of a suitably programmed computer. In a unit claim enumerating a number of devices, several of these devices may be embodied by the same hardware item. The use of the words first, second, and third, etc. does not indicate any order. These words may be interpreted as names. The steps in the above embodiments, unless otherwise specified, should not be understood as limitations on the order of execution.

Claims

1. A method for detecting rule conflicts in intelligent building systems based on statistical model verification, characterized in that: include: Step 1: Based on the price-time automaton network, a rule model of the intelligent building system is constructed, and the execution action reachability of each rule defined in the rule model of the intelligent building system is calculated by using statistical model checking technology; Step 2: Based on the reachability of the execution action of each rule, determine whether the intelligent building system has rule loop conflicts, execution action conflicts, time-space intersection conflicts, condition coverage conflicts, system constraint conflicts, trigger condition conflicts, rule coverage conflicts or execution result conflicts.

2. The intelligent building system rule conflict detection method based on statistical model verification according to claim 1, characterized in that: The intelligent building system rule model is a five-tuple R:<T,A,R,P,C> ;in: T represents the triggering conditions of the rule, which include: system time, variable exceeding the limit, and device status change; A represents the corresponding system operation (Actions) when the conditions are met. The system operation includes: equipment start and stop, parameter setting and subsystem linkage. A is represented by an assignment function; R represents the rule action area (Region). The trigger condition T and system operation A during rule definition act on the global scope. When region R is set, the rule acts on the monitoring variables and device actions within this region. P represents the priority of the rule. The default priority of a rule is 1 when it is defined. Users can modify the priority according to actual business needs and equipment measurement and control requirements. Rules with higher priorities are executed before rules with lower priorities. C represents the constraints for rule execution. Under default conditions, no constraints are set for the rule. When the trigger condition T is met, the system operation A can be executed, that is, T→A. When the constraint C is set, the trigger condition T is met and the constraint is met at the same time, the system operation A can be executed, that is, T,C→A.

3. The intelligent building system rule conflict detection method based on statistical model verification according to claim 2, characterized in that: The step of calculating the execution action reachability of each rule defined in the intelligent building system rule model by using the statistical model checking technology in step 1 includes: The weighted metric temporal logic is adopted to determine the reachability expression of the rule execution action, and the rule execution action reachability expression and the intelligent building system rule model are loaded into the target statistical model verification tool to calculate the execution action reachability of each rule defined by the intelligent building system rule model.

4. The intelligent building system rule conflict detection method based on statistical model verification according to claim 3 is characterized in that: The reachability expression of the rule execution action is: Pr[<=Time](Ai), which represents the reachability of the execution action of the i-th rule within the time of Time.

5. The intelligent building system rule conflict detection method based on statistical model checking according to claim 3, characterized in that: The target statistical model verification tool is UPPAAL-SMC.

6. The intelligent building system rule conflict detection method based on statistical model checking according to claim 4, characterized in that: Step 2 includes: Step 2-1: When the statistical model test result shows that Zeno behavior exists, if there are at least two rules that meet the preset conditions, it is determined that the intelligent building system has a rule cycle conflict; otherwise, it is determined that the intelligent building system does not have a rule cycle conflict; Step 2-2: When the execution action reachability of any rule is less than 90%, judging whether the intelligent building system has execution action conflict, time-space intersection conflict or condition coverage conflict according to the rules containing the same action variables obtained by traversing all the rules; Step 2-3: When the execution action reachability of any rule is greater than or equal to 90%, it is determined whether the intelligent building system has a system constraint conflict, a trigger condition conflict, a rule coverage conflict or an execution result conflict.

7. The intelligent building system rule conflict detection method based on statistical model checking according to claim 6, characterized in that: Step 2-1 also includes: When the statistical model test results show that there is no Zeno behavior, it is determined whether the execution action reachability of any rule is less than 90%.

8. The intelligent building system rule conflict detection method based on statistical model verification according to claim 6, characterized in that: The preset condition is that the execution action of the first rule of each two adjacent rules is equal to the triggering condition of the second rule, and the execution action of the last rule is equal to the triggering condition of the first rule.

9. The intelligent building system rule conflict detection method based on statistical model checking according to any one of claims 6 to 8, characterized in that: Step 2-2 includes: Step 2-2-1: When the execution action reachability of any rule is less than 90%, traverse the rules containing the same action variables in all rules to obtain at least one two-element set Dk{Rki, Rkj}; where Dk is the k-th two-element set, Rki is the i-th rule in the k-th two-element set, and Rkj is the j-th rule in the k-th two-element set; Step 2-2-2: For the two rules Rki and Rkj in the two-element set Dk, then Tki∩ When Aki≠Akj, it is determined that there is an execution action conflict between Rki and Rkj, otherwise, it is determined that there is no execution action conflict between Rki and Rkj; wherein Tki is the trigger condition of the i-th rule in the k-th two-element set, Tkj is the trigger condition of the j-th rule in the k-th two-element set, Aki is the execution action of the i-th rule in the k-th two-element set, and Akj is the execution action of the j-th rule in the k-th two-element set; Step 2-2-3: For the two rules Rki and Rkj in the two-element set Dk, when Tki(t)==True and Tkj(t)==True and Aki≠Akj, it is determined that there is a time-space crossover conflict between Rki and Rkj, otherwise, it is determined that there is no time-space crossover conflict between Rki and Rkj; Step 2-2-4: For the two rules Rki and Rkj in the two-element set Dk, when Tki→Tkj or Tkj→Tki and Aki=Akj, it is determined that there is a conditional coverage conflict between Rki and Rkj; otherwise, it is determined that there is no conditional coverage conflict between Rki and Rkj.

10. The intelligent building system rule conflict detection method based on statistical model checking according to claim 9, characterized in that: Steps 2-3 include: Step 2-3-1: Verify whether each rule whose execution action reachability is greater than or equal to 90% satisfies the corresponding constraint condition; if any rule does not satisfy the corresponding constraint condition, it is determined that there is a system constraint conflict in the intelligent building system; otherwise, it is determined that there is no system constraint conflict in the intelligent building system; Step 2-3-2: Verify whether the reachability of the reverse action of each rule whose execution action reachability is greater than or equal to 90% is greater than 10%. If the reachability of the reverse action of any rule is greater than 10%, it is determined that there is a trigger condition conflict in the intelligent building system. Otherwise, it is determined that there is no trigger condition conflict in the intelligent building system. Step 2-3-3: For the two rules Rki and Rkj in the two-element set Dk, when Tki==Tkj and When , it is determined that the intelligent building system has rule coverage conflicts; when all the two-element sets do not satisfy Tki==Tkj and It is determined that there is no rule coverage conflict in the intelligent building system; Step 2-3-4: Use the statistical model verification tool UPPAAL-SMC to simulate the action variables in each rule Ai. If the action variables of any rule oscillate or the simulation is invalid, it is determined that there is an execution result conflict in the intelligent building system. If the action variables of all rules do not oscillate or the simulation is invalid, it is determined that there is no execution result conflict in the intelligent building system.

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