Fault positioning method and device, electronic equipment and storage medium

Abstract

The application discloses a fault positioning method and device, electronic equipment and storage medium, the method comprises: the fault monitoring device applied to the smoke alarm system, the smoke alarm system further comprises n smoke alarms, n is a positive integer, first, through the fault monitoring device, obtain the device running monitoring data of each smoke alarm in the n smoke alarms in a preset time period, obtain n groups of device running monitoring data, then determine the n fault probability values corresponding to the n smoke alarms based on the n groups of device running monitoring data, then determine the k fault probability values greater than the preset fault probability threshold value in the n fault probability values, finally, determine that the k smoke alarms corresponding to the k fault probability values have faults. The fault positioning efficiency of the smoke alarm is improved by adopting the application embodiment.

Description

Technical Field

[0001] This invention relates to the field of fault location technology for smoke detectors, and more particularly to a fault location method, device, electronic equipment, and storage medium. Background Technology

[0002] Smoke detectors are the first line of defense for fire safety in buildings. They are widely installed in various indoor locations such as residences, shops, office buildings, and factories, allowing sufficient time for evacuation and fire rescue, effectively reducing personal injury and property damage caused by fire. Deploying multiple smoke detectors within a building area can achieve full-area fire monitoring, providing continuous 24 / 7 coverage.

[0003] Currently, because multiple smoke detectors are deployed in a unified manner and operate independently, it is impossible to automatically screen for devices with potential malfunctions in batches. Staff can only manually inspect and troubleshoot each device on-site, resulting in low efficiency in locating faults in smoke detectors. Therefore, improving the efficiency of fault location for smoke detectors is an urgent problem to be solved. Summary of the Invention

[0004] This application provides a fault location method that improves the fault location efficiency of smoke alarms.

[0005] In a first aspect, embodiments of this application provide a fault location method applied to a fault monitoring device of a smoke alarm system, wherein the smoke alarm system further includes n smoke detectors, where n is a positive integer, and the method includes: The fault monitoring device acquires the equipment operation monitoring data of each of the n smoke alarms within a preset time period, resulting in n sets of equipment operation monitoring data. Based on the n sets of equipment operation monitoring data, n fault probability values ​​are determined for the n smoke alarms; each smoke alarm corresponds to one fault probability value; the fault probability value is used to characterize the probability of the smoke alarm malfunctioning; Determine k fault probability values ​​from the n fault probability values ​​that are greater than a preset fault probability threshold; k is an integer less than or equal to n; The k smoke detectors corresponding to the k failure probability values ​​are determined to have malfunctioned.

[0006] Secondly, this application provides a fault location device for a fault monitoring device applied to a smoke alarm system. The smoke alarm system further includes n smoke alarms, where n is a positive integer. The device includes an acquisition unit and a processing unit. The acquisition unit is used to acquire the equipment operation monitoring data of each of the n smoke alarms within a preset time period through the fault monitoring device, and obtain n sets of equipment operation monitoring data. The processing unit is used to determine n fault probability values ​​corresponding to the n smoke alarms based on the n sets of equipment operation monitoring data; each smoke alarm corresponds to a fault probability value; the fault probability value is used to characterize the probability of the smoke alarm malfunctioning; Determine k fault probability values ​​from the n fault probability values ​​that are greater than a preset fault probability threshold; k is an integer less than or equal to n; The k smoke detectors corresponding to the k failure probability values ​​are determined to have malfunctioned.

[0007] Thirdly, embodiments of the present invention provide an electronic device, including: a processor, a memory, a communication interface, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the processor to cause the electronic device to perform the method as described in the first aspect.

[0008] Fourthly, embodiments of the present invention provide a computer-readable storage medium storing a computer program that is executed by a processor to implement the method as described in the first aspect.

[0009] Fifthly, embodiments of the present invention provide a computer program product including a non-transitory computer-readable storage medium storing a computer program, such that a computer performs the method as described in the first aspect.

[0010] Implementing the embodiments of the present invention has the following beneficial effects: As can be seen, the fault location method described in this embodiment of the invention is applied to the fault monitoring device of a smoke alarm system. The smoke alarm system further includes n smoke alarms, where n is a positive integer. First, the fault monitoring device acquires the equipment operation monitoring data of each of the n smoke alarms within a preset time period, obtaining n sets of equipment operation monitoring data. Then, based on the n sets of equipment operation monitoring data, n fault probability values ​​corresponding to the n smoke alarms are determined. Next, k fault probability values ​​among the n fault probability values ​​that are greater than a preset fault probability threshold are determined. Finally, the k smoke alarms corresponding to the k fault probability values ​​are determined to have failed, thereby improving the fault location efficiency of the smoke alarm. Attached Figure Description

[0011] To more clearly illustrate the technical solutions in the embodiments of this application or the background art, the accompanying drawings used in the embodiments of this application or the background art will be described below.

[0012] Figure 1 This is an application scenario diagram of a smoke alarm system provided in the embodiments of this application; Figure 2 This is a flowchart of a fault location method provided in an embodiment of this application; Figure 3 This is a flowchart of an embodiment of the present application for determining the fault probability value corresponding to a first smoke alarm; Figure 4 This is a flowchart of a method for determining a target interference coefficient provided in an embodiment of this application; Figure 5 This is a flowchart of a fault indication method provided in an embodiment of this application; Figure 6 This is a layout diagram of a fault indication device provided in an embodiment of this application; Figure 7 This is a schematic diagram of the structure of a fault location device provided in an embodiment of this application; Figure 8 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0013] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present application.

[0014] The terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish different objects, not to describe a specific order. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or apparatuses.

[0015] In this document, the term "implementation" means that a specific feature, structure, or characteristic described in connection with an implementation may be included in at least one implementation of this application. The appearance of this phrase in various places in the specification does not necessarily refer to the same implementation, nor is it a separate or alternative implementation mutually exclusive with other implementations. It will be explicitly and implicitly understood by those skilled in the art that the implementations described herein can be combined with other implementations.

[0016] Please see Figure 1 , Figure 1 This is an application scenario diagram of a smoke alarm system provided in the embodiments of this application.

[0017] In the application scenario of this embodiment, the smoke alarm system includes smoke alarm 1, smoke alarm 2, smoke alarm 3, smoke alarm 4, and fault monitoring equipment.

[0018] The fault monitoring equipment of the smoke alarm system acquires the equipment operation monitoring data of smoke alarms 1, 2, 3, and 4 within a preset time period through the transmission channel shown by the dotted line in the diagram. This results in four sets of independent equipment operation monitoring data. Based on these four sets of data, four fault probability values ​​are calculated for each smoke alarm (1, 2, 3, and 4). Each fault probability value represents the likelihood of a corresponding smoke alarm malfunctioning. These four fault probability values ​​are then compared to a preset fault probability threshold. Fault probability values ​​exceeding this threshold are selected. For example, if two fault probability values ​​exceed the threshold, the two smoke alarms corresponding to these two values ​​are identified. If these two smoke alarms are smoke alarm 1 and smoke alarm 3, then smoke alarm 1 and smoke alarm 3 are confirmed to be faulty. The system can then notify maintenance personnel that smoke alarm 1 and smoke alarm 3 have malfunctioned and require repair.

[0019] It's important to explain that in actual operation, the number and installation location of smoke detectors are flexibly adjusted according to fire safety regulations such as building floors, room area, and fire compartments. Therefore, the installation locations of smoke detectors can be quite complex. If maintenance personnel were to conduct on-site fault tests on each smoke detector individually, they would need to travel floor by floor and room by room for inspection. This not only consumes a lot of time and energy but also results in low overall fault detection efficiency and the risk of missing some devices in certain corners. However, if fault monitoring equipment is used to monitor smoke detectors in an area, maintenance personnel do not need to manually test each detector on-site. Even if there are many smoke detectors in a building and they are scattered, the fault monitoring equipment can complete the fault risk assessment of all devices at once and quickly identify the target detectors with excessive fault probability. Maintenance personnel only need to go directly to the corresponding floor and fire compartment based on the fault location information provided by the smoke alarm system to repair or replace the faulty smoke detector, which greatly improves the fault detection efficiency of smoke detectors.

[0020] It should be explained that, in this embodiment, the smoke alarm system may further include interconnected communication devices, which include n interconnected communication units, each of which is installed within a smoke alarm. Taking any one of the n smoke alarms, namely the first smoke alarm, as an example, the interconnected communication devices will be described in detail. The first interconnected communication unit is installed within the first smoke alarm, and is the interconnected communication unit among the n interconnected devices that corresponds to the first smoke alarm.

[0021] In this embodiment, the first interconnection communication device may include a level driving unit, a frame encapsulation unit, a cyclic redundancy check unit, and a pulse width coding modulation unit. Specifically, the level driving unit is used to output a preset alarm level compatible with the first smoke alarm; the frame encapsulation unit is used to encapsulate the initial device operation monitoring data corresponding to the first smoke alarm to obtain a reporting message, the reporting message including the device identifier of the first smoke alarm; the cyclic redundancy check unit is used to filter out erroneous data in the reporting message to obtain a target reporting message, the monitoring data corresponding to the target reporting message being the first set of device operation monitoring data; the pulse width coding modulation unit is used to modulate the target reporting message into a pulse width waveform, superimpose the pulse width waveform onto the preset alarm level, and transmit it to the fault monitoring device, so that the fault monitoring device can obtain the first set of device operation monitoring data.

[0022] In this embodiment, the first interconnection communication device is a functional circuit module group integrated inside the first smoke alarm, used to realize X-LINK-V2 protocol interconnection communication.

[0023] The level driving unit is used to drive the hardware circuitry of the interconnect signal line. It can output a preset alarm level compatible with older hard-wired smoke detectors. When the first smoke detector detects smoke, wiring faults, or other alarm events, the level driving unit uses a pull-up circuit to stably pull the interconnect signal line to the preset alarm level and maintain it for a specified duration. Older alarms that only support basic level recognition on the line can trigger a local alarm when the voltage reaches the judgment threshold. This ensures interoperability between new and old devices while providing a stable base voltage carrier for superimposed digital coded waveforms. For example, the preset alarm level can be a 9V DC voltage. When the first smoke detector detects smoke, wiring faults, or other alarm events, the level driving unit uses a pull-up circuit to stably pull the interconnect signal line to 9V and maintain it for 300ms. Older alarms that only support basic level recognition on the line have a 6V judgment threshold. When the interconnect signal line voltage continuously exceeds this 6V threshold, the older alarm determines that an alarm signal exists on the line and triggers a local alarm simultaneously.

[0024] The frame encapsulation unit is used to structurally assemble various raw data from the first smoke alarm, including smoke alarms, fault alarms, and device self-tests. It sequentially fills in information such as the frame synchronization header, the unique device identifier of the first smoke alarm, the event type, the forwarding hop count, and the timestamp according to a preset frame format, generating a complete reporting message. The device identifier carried in the message can uniquely identify each alarm device, solving the problem of traditional interconnection methods being unable to distinguish the alarm source. For example, a fixed 24-byte frame format can be used to sequentially fill in information such as a two-byte frame synchronization header, a three-byte unique 24-bit device identifier for the first smoke alarm, the root device identifier, a one-byte event type, a one-byte forwarding hop count, a four-byte timestamp, and reserved fields to generate a complete reporting message. The frame synchronization header is fixed as two sets of hexadecimal identifiers, the event type can distinguish different alarm scenarios such as smoke alarms and wiring polarity errors, and the device identifier carried in the message can uniquely identify each alarm device.

[0025] It should be explained that the fault monitoring device in the smoke alarm system can parse the target reporting message to obtain the unique device identifier of the first smoke alarm. Based on a pre-established device identifier mapping relationship, it can first determine the device identifier information corresponding to the unique device identifier, and then report the device identifier information and the event information corresponding to the first smoke alarm to the smoke alarm system's server via the network. This allows the terminal devices of the smoke alarm system to display the device identifier information and event information corresponding to the first smoke alarm. The Cyclic Redundancy Check (CR) unit receives the reporting message output by the frame encapsulation unit, performs calculations on the overall data of the message to generate a CR code, and appends it to the end of the message, generating a verified target reporting message. During operation, interconnection lines are susceptible to power grid spikes, lightning strikes, and electromagnetic interference, causing data distortion. The receiving device will recalculate the check code and compare it with the check code already present in the message. If they do not match, the distorted message is discarded. This filters out erroneous data during transmission, ensuring the integrity and accuracy of transmitted device operation monitoring data and preventing false alarms or missed alarms. For example, an eight-bit cyclic redundancy check (CRC) code can be generated from all the data in a complete reporting message. The calculation process uses a fixed polynomial. The generated eight-bit check byte is appended to the end of the twenty-four-byte message to form a complete target reporting message. When the receiving device parses the message, it recalculates the check code synchronously. If the two sets of check code values ​​are inconsistent, the current message is discarded directly, and the device alarm information carried in it is not parsed.

[0026] The pulse width encoding modulation unit is used to convert the target reporting message output by the cyclic redundancy check unit into the corresponding pulse width modulation waveform. Based on the preset alarm level output by the level drive unit, a pulse waveform that distinguishes logic 0 and logic 1 is generated by a small periodic voltage pull-down. This pulse width waveform is then superimposed on a stable preset alarm level and transmitted to other fault monitoring devices on the line through the interconnect signal line. Small voltage fluctuations will not affect the recognition of the basic alarm level by older alarm devices. Newer devices with demodulation capabilities can analyze the pulse width waveform through the filter circuit to restore complete equipment operation monitoring data, enabling the simultaneous transmission of general alarm levels and refined equipment digital information on a single interconnect line. For example, the 9-volt preset alarm level output by the level drive unit can be used as a base. By periodically pulling the voltage down to 7 volts, a pulse waveform can be generated to distinguish logic levels. A 7-volt pulse lasting 400 microseconds represents logic 1, and a 7-volt pulse lasting 200 microseconds represents logic 0. A stable 9-volt interval of 900 microseconds is set between adjacent bits. The overall amplitude fluctuation of the pulse width waveform is only two volts peak-to-peak. This pulse width waveform is superimposed on a stable 9-volt level and transmitted to other fault monitoring devices on the line through the interconnect signal line. Small voltage fluctuations will not affect the recognition of the basic alarm level by older alarms. Newer devices with demodulation capabilities can analyze the pulse width waveform through a 20 kHz high-pass filter circuit to restore complete equipment operation monitoring data, thereby enabling the simultaneous transmission of general alarm levels and refined equipment digital information on a single interconnect line.

[0027] It should be explained that the first interconnection communication device may further include a power-on debounce unit and a wiring self-diagnosis unit. The power-on debounce unit is used to perform debounce operations on the first smoke alarm based on a preset power-on debounce duration when the first smoke alarm is powered on, to prevent false alarms. The wiring self-diagnosis unit is used to perform cross-comparison detection on the power supply live wire, power supply neutral wire, and communication signal line connected to the first smoke alarm to identify the corresponding wiring misconnection fault. When the first smoke alarm experiences the wiring misconnection fault, it provides a prompt according to the preset wiring misconnection fault prompt operation.

[0028] The power-on debouncing unit is used during the power-on startup phase of the first smoke alarm. Based on a preset power-on debouncing duration, it shields and debounces the level fluctuations of the interconnecting signal lines, filtering out instantaneous voltage oscillations caused by plugging and unplugging power supply terminals. This prevents the first smoke alarm from misinterpreting power-on transient jitter as interconnecting alarm signals, thus preventing simultaneous false alarms from all types of alarms in the house. For example, the preset power-on debouncing duration can be set to 800 milliseconds. After the first smoke alarm completes its power-on self-test, it immediately enters this debouncing duration window. During this window, any level fluctuations in the interconnecting signal lines will not trigger the interconnecting alarm logic. One hundred milliseconds before the end of the debouncing window, the first smoke alarm performs stable sampling of the interconnecting signal lines. If the sampled voltage remains consistently low, it determines that the line is normal and directly enters normal monitoring mode. If the sampled voltage shows a stable level consistently higher than the judgment threshold, it is identified as a real alarm from other smoke alarms on the line, and the alarm and data parsing process are executed simultaneously.

[0029] The wiring self-diagnostic unit is used to simultaneously collect the voltage difference and ground impedance parameters of the three lines connected to the first smoke alarm: the live power line, the neutral power line, and the communication signal line. By cross-comparing multiple sets of electrical parameters, it completes the detection of the wiring status and accurately identifies various wiring faults such as live and neutral wire swapping, live wire and communication line reversed, neutral wire and communication line reversed, and communication line suspended. Once the detection confirms that the first smoke alarm itself has a wiring fault, the first smoke alarm will continuously output an alarm according to the preset exclusive audible and visual prompts, which makes it convenient for installers to quickly locate the faulty device. For example, the first smoke alarm will simultaneously collect data on the voltage between the live wire and neutral wire, the voltage between the live wire and communication wire, the voltage between the neutral wire and communication wire, and the impedance data of the three lines to ground. It will then perform cross-judgment by comparing the data with preset standard parameter ranges. If a wiring error is detected, the first smoke alarm will continuously output a unique buzzer with three short beeps and one long beep. Each short beep lasts for 200 milliseconds with an interval of 100 milliseconds, and the long beep lasts for 800 milliseconds. After one round of beeping, it will remain silent for 10 seconds before triggering a cycle. If the line is equipped with a new smoke alarm with a gateway function, the gateway device can also simultaneously upload the type of misconnection fault and the unique device identifier of the first smoke alarm to the mobile terminal, intuitively displaying the specific wiring error type.

[0030] Please see Figure 2 , Figure 2 This is a flowchart of a fault location method provided in an embodiment of this application, applied to a fault monitoring device of a smoke alarm system. The smoke alarm system further includes n smoke detectors, where n is a positive integer. The method includes, but is not limited to, the following steps: S201: Obtain the equipment operation monitoring data of each of the n smoke detectors within a preset time period to obtain n sets of equipment operation monitoring data.

[0031] In this embodiment, the fault monitoring device can be a dedicated fire monitoring gateway, a fire zone monitoring host, or an embedded data processing terminal that is set up independently. The fault monitoring device has the core features of multi-point parallel data reception, multi-channel independent data storage, and batch data processing. It supports simultaneous connection to multiple smoke detectors deployed in the building and can manage the data uploaded by each smoke detector in a separate group. The data from smoke detectors at different locations will not interfere with each other.

[0032] The fault monitoring equipment can be flexibly installed in the building's fire protection layout. It can be centrally installed in the fire control room of the entire building to uniformly manage all smoke detectors in the building, or it can be arranged in the low-voltage rooms corresponding to different fire compartments.

[0033] The fault monitoring device can increase the number of communication interfaces according to the number of connected smoke alarms. The transmission link can be either wired or wireless. One fault monitoring device can complete the fault detection of all smoke alarms in the entire area.

[0034] A one-to-one data transmission link can be established between the fault monitoring device and n smoke detectors using wired or wireless communication. Figure 1 The transmission channel shown by the dashed line indicates that each smoke alarm is independently assigned a dedicated transmission channel to connect with the fault monitoring device. This prevents data congestion and errors caused by multiple smoke alarms sharing a single path for data transmission. Within a preset time period, each smoke alarm continuously collects its own equipment operation monitoring data and uploads it unidirectionally to the fault monitoring device in real time through its dedicated transmission channel. The fault monitoring device can receive monitoring data synchronously sent from all n transmission channels in parallel, thereby obtaining the equipment operation monitoring data of each of the n smoke alarms within the preset time period, resulting in n sets of equipment operation monitoring data.

[0035] In this embodiment, the equipment operation monitoring data uploaded by each smoke alarm to the fault monitoring device can include two types of data: line transmission monitoring data and status reporting monitoring data.

[0036] Line transmission monitoring data is used to characterize the operating conditions of the transmission channel between smoke alarms and fault monitoring equipment. Specifically, it includes parameters such as data packet transmission and reception statistics, data transmission packet loss rate, line voltage fluctuation value, transmission signal signal-to-noise ratio, line short circuit or open circuit identification signal, and single data transmission delay. It can reflect whether there are faults at the transmission link level, such as poor line contact, line aging, or external signal interference.

[0037] Status reporting monitoring data can be generated by each smoke alarm actively performing timed status reporting operations according to a pre-set fixed reporting cycle. Every preset time interval, the smoke alarm automatically collects its own hardware operating information and performs the reporting operation. Not only can it periodically collect the hardware operating information of the smoke alarm, but it can also verify whether each smoke alarm completes the reporting action on time. If the fault monitoring device does not receive the status reporting data of a smoke alarm within the corresponding cycle, it determines that the smoke alarm has abnormal fault potentials such as communication interruption, power failure, or hardware crash. At this time, the probability of the smoke alarm malfunctioning will be greater.

[0038] S202: Determine the n fault probability values ​​corresponding to the n smoke alarms based on the n sets of equipment operation monitoring data.

[0039] In this embodiment, each smoke alarm corresponds to a fault probability value; the fault probability value is used to characterize the probability that the smoke alarm will malfunction.

[0040] The probability of a smoke alarm malfunction can be determined by using the equipment operation monitoring data obtained from the fault monitoring device. Specifically, the message transmission failure frequency and alarm linkage signal response duration of the smoke alarm within a preset time period can be determined first based on the line transmission monitoring data. Then, a reference fault probability value can be determined based on the message transmission failure frequency and the alarm linkage signal response duration. At the same time, the status reporting timeliness rate of the smoke alarm within the preset time period can be determined based on the status reporting timeliness rate, and an optimization factor corresponding to the status reporting timeliness rate can be determined. Finally, the reference fault probability value can be optimized based on the optimization factor to determine the fault probability value corresponding to the smoke alarm.

[0041] S203: Determine k fault probability values ​​from the n fault probability values ​​that are greater than a preset fault probability threshold.

[0042] In this embodiment, k is an integer less than or equal to n. The preset fault probability threshold is a value stored in advance within the fault monitoring device to distinguish between the normal operation state and the fault state of the smoke alarm. The preset fault probability threshold can be determined by combining data such as the size of the building fire compartment, the number of smoke alarms deployed on site, the standard operating parameters of the equipment at the factory, historical fault sample data, and fire protection operation and maintenance management requirements. For example, simulation tests can be conducted to simulate various fault conditions such as line interference, equipment power failure, sensor aging, and timed reporting timeout to calculate the average fault probability corresponding to various abnormal conditions, thereby determining the preset fault probability threshold.

[0043] After determining the n fault probability values ​​corresponding to the n smoke detectors, it is possible to identify k fault probability values ​​that are greater than a preset fault probability threshold.

[0044] S204: Determine that the k smoke detectors corresponding to the k fault probability values ​​have malfunctioned.

[0045] In this embodiment, after determining k fault probability values ​​out of the n fault probability values ​​that are greater than a preset fault probability threshold, each of the k fault probability values ​​exceeding the threshold can be reverse-matched to obtain k smoke detectors corresponding to the k fault probability values. If the k smoke detectors corresponding to the k fault probability values ​​are found to be faulty, the fault information can be determined based on the original monitoring data such as the device number of the k smoke detectors, the floor where they are installed, the fire compartment to which they belong, the fault probability value, and any abnormal line transmission or status reporting timeout that caused the risk. On-site reminders can be provided through a pop-up display and an audible and visual warning device. Alternatively, the fault information can be pushed to the operation and maintenance management terminal via a transmission channel. Operation and maintenance personnel can view the fault information through the operation and maintenance management terminal, thereby improving the fault location efficiency of the smoke detectors.

[0046] As can be seen, by acquiring the equipment operation monitoring data of smoke detectors in the area based on the fault monitoring equipment, and then locating the faulty smoke detectors based on the equipment operation monitoring data, it can adapt to the complex scenario of a large number of dispersed smoke detectors being deployed in buildings according to the floors, room areas, and fire compartment specifications. It eliminates the need for maintenance personnel to conduct on-site inspections of smoke detectors one by one, significantly reducing manpower input and inspection time, and improving fault detection efficiency. By determining the probability of fault occurrence through multiple monitoring data such as message transmission and timed reporting, the fault identification accuracy is higher, and high-risk faulty equipment can be directly located. It can quickly determine the precise fault location information, helping maintenance personnel to carry out fault repair operations, thereby greatly improving the fault location efficiency of smoke detectors.

[0047] It should be explained that the smoke alarm in this embodiment can be a hard-wired interconnected smoke alarm. In addition to the external factors mentioned in this embodiment, the smoke alarm may also malfunction due to internal factors.

[0048] For example, due to confusion in the wiring sequence of the live wire, neutral wire, and interconnection line during installation, or due to unconnected lines, the power supply and interconnection communication lines of the smoke alarm may be in an abnormal working condition. This can result in anything from failing to synchronize with other smoke alarms to the entire interconnection line malfunctioning, and even interfering with the normal communication of other smoke alarms on the line. To mitigate this, the voltage of the live wire, neutral wire, and interconnection line can be collected simultaneously during the smoke alarm's power-on self-test. At the same time, the impedance values ​​of each of the three lines to ground can be measured. The collected voltage and impedance data can be cross-compared with the standard parameters of normal wiring. If the parameters do not match and the abnormal state is maintained stably for a certain period of time, the smoke alarm can be controlled to emit a unique fault warning sound. The gateway associated with the line will also read this abnormal signal and upload it to the backend, determining that an internal fault has occurred in the smoke alarm.

[0049] For example, due to the aging of the smoke alarm's built-in storage components and the failure of its read / write function, it may be unable to stably retain its own unique identifier, periodic heartbeat records, and fault operation logs. The gateway may not be able to read the information of this smoke alarm, and the backend will mark the smoke alarm as offline and periodically listen to the heartbeat interaction signals periodically emitted by all smoke alarms on the line. If the gateway does not receive the smoke alarm's identifier and heartbeat data for a long time, it can determine that its storage components have been damaged.

[0050] For example, the hardware circuitry responsible for signal acquisition and noise filtering within the smoke alarm may be damaged, making it impossible to distinguish between the basic level of the interconnecting lines and the coded communication signals. This can lead to frequent data transmission failures and data verification failures between smoke alarms, causing communication transmission faults. The voltage signal acquired from the interconnecting lines can be decomposed into waveforms, and the transmitted data can be verified. If the same smoke alarm repeatedly experiences data transmission failures and verification failures, it can be determined that its signal acquisition and filtering hardware circuitry is faulty.

[0051] For example, the voltage divider sampling circuit used for voltage and impedance detection inside the smoke alarm may also fail. After power-on, it cannot complete the cross-comparison of the voltage and impedance to ground of the three lines (live wire, neutral wire, and interconnecting wire), and cannot automatically identify wiring errors. Long-term operation in abnormal circuit environments will aggravate the failure of the whole machine. During the power-on self-test of the smoke alarm, the voltage and impedance to ground parameters of the three lines can be collected simultaneously. By cross-comparing multiple sets of parameters with standard values, if there are wiring errors but no fault warning is output, it can be determined that the voltage divider impedance detection circuit is damaged.

[0052] For example, the smoke alarm may also fail to emit a dedicated fault warning sound if the drive circuit controlling the fault warning sound output is damaged. When the smoke alarm detects a wiring error or its own malfunction, it will be unable to emit a dedicated fault warning sound, and the fault sound reminder function will be directly disabled. During the power-on self-test phase of the smoke alarm, you can check the simulated wiring error, its own malfunction, and other operating conditions, and actively start the fault warning sound output logic. If no corresponding warning sound is emitted during the entire self-test, it can be determined that the sound driving circuit has failed.

[0053] For example, the aging of the smoke and carbon monoxide sensors in the smoke alarm may cause the voltage sampling circuit to drift, frequently triggering false alarms when there is no fire, and failing to properly identify alarms when a real fire occurs, continuously pushing abnormal event information outwards. It can continuously collect the gas concentration value in the sensing cavity and continuously compare it with the preset trigger threshold. If there are frequent alarms when there is no dangerous gas, or no alarm feedback for a long time when there is dangerous gas, it can be determined that the sensing device and sampling circuit are malfunctioning.

[0054] When the first set of equipment operation monitoring data includes line transmission monitoring data and status reporting monitoring data, the first set of equipment operation monitoring data is the equipment operation monitoring data corresponding to the first smoke alarm. The first smoke alarm is any one of the n smoke alarms. Please refer to [link / reference]. Figure 3 , Figure 3 This application provides a flowchart for determining the fault probability value corresponding to a first smoke alarm, including but not limited to the following steps: S301: Based on the line transmission monitoring data, determine the message transmission failure frequency and alarm linkage signal response duration of the first smoke alarm within the preset time period.

[0055] In this embodiment, the total number of all interactive messages and status reporting messages sent by the first smoke alarm to the fault monitoring device within the preset time period, as well as the number of failed messages that the fault monitoring device failed to fully receive and identify due to problems such as line short circuits, signal interference, message verification errors, transmission timeouts, and link disconnections, are obtained. The message transmission failure frequency is obtained by dividing the number of failed messages by the total number of messages sent. The message transmission failure frequency can characterize the communication stability of the communication link between the smoke alarm and the fault monitoring device. The higher the value of the message transmission failure frequency, the more frequent the line transmission abnormality problem.

[0056] Within the preset time period, the starting time when the first smoke alarm triggers an alarm and sends an alarm linkage signal is determined. Simultaneously, the ending time when the fault monitoring device fully receives and parses the valid alarm linkage message is recorded. The time difference between the ending and starting times is calculated to obtain the response time of a single alarm linkage signal. The average response time of all alarm linkage events generated by the smoke alarm within the preset time period is calculated to obtain the alarm linkage signal response time corresponding to the first smoke alarm. The alarm linkage signal response time characterizes the data interaction efficiency of the communication link between the smoke alarm and the fault monitoring device. A higher alarm linkage signal response time indicates more severe transmission link problems such as line signal attenuation, communication congestion, and transmission delay.

[0057] S302: Determine a reference fault probability value based on the message transmission failure frequency and the alarm linkage signal response time.

[0058] In this embodiment, a first reference fault probability value corresponding to the message transmission failure frequency and a second reference fault probability value corresponding to the alarm linkage signal response time can be determined first. Then, a third reference fault probability value can be determined based on the first reference fault probability value and the second reference fault probability value. Next, the voltage change data of the power supply voltage source that supplies power to the first smoke alarm can be obtained through the power quality acquisition module. Then, the target interference coefficient can be determined based on the voltage change data. Finally, the third reference fault probability value can be adjusted based on the target interference coefficient to obtain the reference fault probability value.

[0059] For example, a first reference fault probability value corresponding to the message transmission failure frequency and a second reference fault probability value corresponding to the alarm linkage signal response time are determined. Specifically, this can be a first mapping relationship between the message transmission failure frequency and the fault probability value. Based on this first mapping relationship, the first reference fault probability value corresponding to the message transmission failure frequency can be determined.

[0060] It can be a second mapping relationship between the alarm linkage signal response time and the fault probability value. Based on this second mapping relationship, a second reference fault probability value corresponding to the alarm linkage signal response time can be determined.

[0061] For example, a third reference fault probability value is determined based on the first reference fault probability value and the second reference fault probability value. Specifically, a first weight corresponding to the first reference fault probability value and a second weight corresponding to the second reference fault probability value can be determined first, wherein the sum of the first weight and the second weight is 1. Then, the third reference fault probability value is determined based on the first weight, the second weight, the first reference fault probability value, and the second reference fault probability value. Specifically, the third reference fault probability value can be calculated as follows: Third reference failure probability value = First reference failure probability value × First weight + Second reference failure probability value × Second weight; The third reference fault probability value can be determined based on the first weight, the second weight, the first reference fault probability value, and the second reference fault probability value in the manner described above.

[0062] For example, the power quality acquisition module acquires voltage change data of the power supply voltage source that powers the first smoke alarm. Specifically, the fault monitoring device also includes a power quality acquisition module, which can be integrated into the fault monitoring device. It can be used to collect electrical operating conditions on the power supply side of the smoke alarm. The power quality acquisition module can establish an electrical sampling connection with the power supply voltage source corresponding to each smoke alarm. It can collect and record voltage change data such as the fluctuation amplitude, instantaneous voltage drop, voltage surge and drop, and power frequency harmonic distortion of the output voltage of the power supply voltage source in real time within a preset time period. Abnormal power supply voltage will aggravate problems such as line message transmission errors and linkage signal transmission delays. Therefore, it is necessary to acquire voltage change data of the power supply voltage source that powers the first smoke alarm through the power quality acquisition module.

[0063] For example, the target interference coefficient is determined based on the voltage change data. Specifically, the peak voltage duration and peak voltage maximum value can be determined first based on the voltage change data. The peak voltage duration is the duration during which the voltage of the power supply voltage source exceeds a preset voltage threshold within a preset time period, and the peak voltage maximum value is the maximum voltage value of the power supply voltage source exceeding the preset voltage threshold within the preset time period. Then, the voltage difference between the peak voltage maximum value and the preset voltage threshold is determined. Next, a first power quality value corresponding to the peak voltage duration and a second power quality value corresponding to the voltage difference are determined. Finally, the target interference coefficient is determined based on the first power quality value and the second power quality value.

[0064] For example, the reference fault probability value is obtained by adjusting the third reference fault probability value based on the target interference coefficient. Specifically, the reference fault probability value can be determined in the following manner: Reference failure probability value = Third reference failure probability value × (1 + target interference coefficient); The third reference fault probability value can be adjusted based on the target interference coefficient in the manner described above to obtain the reference fault probability value.

[0065] It can be seen that, based on determining the first and second reference fault probability values ​​according to the message transmission failure frequency and alarm linkage signal response time, respectively, and then calculating the third reference fault probability value by fusing the first and second reference fault probability values, a power quality acquisition module is added to the fault monitoring device. This module acquires voltage change data of the power supply voltage source powering the first smoke alarm, determines the target interference coefficient based on the voltage change data, and finally adjusts the third reference fault probability value using the target interference coefficient to obtain the final reference fault probability value. This approach takes into account power quality interference factors on the power supply side, such as grid voltage fluctuations, harmonic distortion, and instantaneous voltage drops. It distinguishes between hardware faults in the communication link itself and temporary transmission anomalies caused by abnormal grid power supply, avoiding misjudgments caused by relying solely on message transmission and linkage response data to determine faults. This ensures that the determined reference fault probability value simultaneously considers the influence of both line communication conditions and power supply environment interference, effectively improving the accuracy of the fault probability results.

[0066] S303: Determine the on-time reporting rate of the first smoke alarm within the preset time period based on the status reporting monitoring data.

[0067] In this embodiment, the total number of times the first smoke alarm needs to send status reporting monitoring data to the fault monitoring device within a preset time period can be obtained first. Then, the number of times the fault monitoring device reports on time within the preset time period can be counted. The number of on-time reports divided by the total number of times the first smoke alarm needs to send status reporting monitoring data to the fault monitoring device can determine the on-time reporting rate of the first smoke alarm within the preset time period.

[0068] S304: Determine the optimization factor corresponding to the on-time reporting rate of the status.

[0069] In this embodiment, it can be a mapping relationship between the reporting timeliness rate and the optimization factor. Based on this mapping relationship, the optimization factor corresponding to the reporting timeliness rate can be determined.

[0070] S305: Optimize the reference fault probability value based on the optimization factor to obtain the fault probability value corresponding to the first smoke alarm.

[0071] In this embodiment, the fault probability value corresponding to the first smoke alarm can be determined in the following manner: The failure probability value of the first smoke alarm = reference failure probability value × (1 + optimization factor); The reference fault probability value can be optimized based on the optimization factor in the above manner to obtain the fault probability value corresponding to the first smoke alarm.

[0072] It should be explained that, in this embodiment, since the first smoke alarm is any one of the n smoke alarms, the method for determining the fault probability value corresponding to the first smoke alarm is the same as the method for determining the n fault probability values ​​corresponding to the n smoke alarms. According to the method for determining the fault probability value corresponding to the first smoke alarm, the n fault probability values ​​corresponding to the n smoke alarms can be determined.

[0073] As can be seen, the reference fault probability value is first determined by extracting two parameters, namely the message transmission failure frequency and the alarm linkage signal response time, from the line transmission monitoring data. Then, the optimization factor is determined by the status reporting monitoring data. Based on the optimization factor, the reference fault probability value obtained solely from the line transmission data is corrected to obtain the final fault probability value of the smoke alarm. This approach can simultaneously integrate information such as communication link transmission stability, data interaction efficiency, and the device's own timed reporting capability, taking into account link problems such as line interference and transmission delay, as well as abnormal information such as inaccurate reporting. This makes the determination of the fault probability value more comprehensive and accurate, thereby improving the reliability of the fault detection results.

[0074] Please see Figure 4 , Figure 4 This is a flowchart of a method for determining a target interference coefficient provided in an embodiment of this application, including but not limited to the following steps: S401: Determine the duration of the peak voltage and the maximum value of the peak voltage based on the voltage change data.

[0075] In this embodiment, the duration of the peak voltage is the duration during which the voltage of the power supply voltage source exceeds a preset voltage threshold within the preset time period, and the maximum value of the peak voltage is the maximum voltage value of the power supply voltage source exceeding the preset voltage threshold within the preset time period.

[0076] After continuously collecting real-time voltage change data from the power supply voltage source within a preset time period by the power quality acquisition module, the voltage value collected at each moment can be compared with the preset voltage threshold in real time. The total duration of all continuous and intermittent periods during which the real-time voltage value is higher than the preset voltage threshold within the preset time period is accumulated. The accumulated total duration is the peak voltage duration. The peak voltage duration can characterize the overall duration of high voltage peak interference on the power supply circuit of the smoke alarm. The larger the peak voltage duration value, the greater the impact of power grid peak voltage interference on the communication transmission of the smoke alarm.

[0077] After continuously collecting real-time voltage change data from the power supply voltage source within a preset time period by the power quality acquisition module, the voltage value collected at each moment can be compared with a preset voltage threshold in real time. All voltage sampling data with real-time voltage values ​​higher than the preset voltage threshold within the preset time period are filtered out, and the voltage sampling value with the largest value is determined. The voltage sampling value with the largest value is the peak voltage maximum value. The peak voltage maximum value can characterize the impact intensity of high voltage peak interference on the power supply circuit of the smoke alarm. The larger the peak voltage maximum value, the stronger the impact amplitude of the power grid peak voltage, and the greater the degree of interference to the communication transmission of the smoke alarm.

[0078] S402: Determine the voltage difference between the maximum peak voltage and the preset voltage threshold.

[0079] In this embodiment, the voltage difference between the maximum peak voltage and the preset voltage threshold can be calculated by the difference between the maximum peak voltage and the preset voltage threshold. The larger the voltage difference between the maximum peak voltage and the preset voltage threshold, the higher the voltage surge intensity.

[0080] S403: Determine the first power quality value corresponding to the duration of the peak voltage and the second power quality value corresponding to the voltage difference.

[0081] In this embodiment, it can be a third mapping relationship between a preset peak voltage duration and a power quality value. Based on this third mapping relationship, a first power quality value corresponding to the peak voltage duration can be determined.

[0082] It can be a fourth mapping relationship between a preset voltage difference and a power quality value. Based on this fourth mapping relationship, a second power quality value corresponding to the voltage difference can be determined.

[0083] S404: Determine the target interference coefficient based on the first power quality value and the second power quality value.

[0084] In this embodiment, a target power quality value can be determined first based on the first power quality value and the second power quality value. Then, an interference coefficient corresponding to the target power quality value is determined to obtain a reference interference coefficient. Next, a voltage waveform distortion coefficient corresponding to the power supply voltage source is determined based on the voltage change data. The voltage waveform distortion coefficient is used to characterize the degree of distortion of the power supply voltage waveform corresponding to the power supply voltage source by clutter interference. Finally, the reference interference coefficient is adjusted based on the voltage waveform distortion coefficient to obtain the target interference coefficient.

[0085] For example, a target power quality value is determined based on the first power quality value and the second power quality value. Specifically, a third weight corresponding to the first power quality value and a fourth weight corresponding to the second power quality value can be determined first, wherein the sum of the third weight and the fourth weight is 1. Then, the target power quality value is determined based on the third weight, the fourth weight, the first power quality value, and the second power quality value. Specifically, the target power quality value can be calculated as follows: Target power quality value = First power quality value × Third weight + Second power quality value × Fourth weight; The target power quality value can be determined based on the third weight, the fourth weight, the first power quality value, and the second power quality value in the manner described above.

[0086] For example, an interference coefficient corresponding to the target power quality value is determined to obtain a reference interference coefficient. Specifically, this can be a preset mapping relationship between power quality values ​​and interference coefficients. Based on this mapping relationship, the interference coefficient corresponding to the target power quality value can be determined to obtain the reference interference coefficient.

[0087] For example, the voltage waveform distortion coefficient corresponding to the power supply voltage source is determined based on the voltage change data. Specifically, the voltage waveform distortion coefficient is used to characterize the degree of distortion of the power supply voltage waveform corresponding to the power supply voltage source due to noise interference.

[0088] In this embodiment, the voltage change data can first be subjected to Fourier transform to obtain the fundamental voltage component and the clutter voltage component corresponding to the power supply voltage source. Then, the effective value of the fundamental voltage corresponding to the fundamental voltage component and the effective value of the clutter voltage corresponding to the clutter voltage component can be determined. Finally, the voltage waveform distortion coefficient can be determined based on the effective value of the fundamental voltage and the effective value of the clutter voltage.

[0089] For example, a Fourier transform is performed on the voltage change data to obtain the fundamental voltage component and clutter voltage component corresponding to the power supply voltage source. Specifically, the voltage change data in the time domain can be determined based on the discrete voltage sampling data arranged in time sequence collected by the power quality acquisition module. The voltage change data in the time domain is input into a preset Fourier transform operation unit to perform spectrum decomposition operation. The time domain voltage signal that changes continuously with time is converted into a frequency domain signal in the frequency dimension through Fourier transform. The frequency signal with the highest energy proportion that is consistent with the power supply standard frequency is extracted from all the frequency components obtained by decomposition as the fundamental voltage component corresponding to the power supply voltage source. All other harmonic and pulse interference frequency signals that deviate from the standard power supply frequency are determined as clutter voltage components, thereby obtaining mutually independent fundamental voltage components and clutter voltage components.

[0090] For example, to determine the effective value of the fundamental voltage corresponding to the fundamental voltage component and the effective value of the clutter voltage corresponding to the clutter voltage component, specifically, firstly, extract all frequency domain sampled values ​​of the fundamental voltage component and the clutter voltage component after Fourier transform separation. For the fundamental voltage component, square all sampled amplitudes of the fundamental voltage component and calculate the average value. Then, perform a square root operation on the average value to calculate the effective value of the fundamental voltage corresponding to the fundamental voltage component. For the clutter voltage component, square all the amplitudes corresponding to the clutter in sequence, calculate the average value, and perform a square root operation to obtain the effective value of the clutter voltage corresponding to the clutter voltage component.

[0091] For example, the voltage waveform distortion coefficient is determined based on the effective value of the fundamental voltage and the effective value of the clutter voltage. Specifically, the square root of the equivalent value of the total clutter energy is taken after dividing the equivalent value of the fundamental energy. The final value is the voltage waveform distortion coefficient. The voltage waveform distortion coefficient can intuitively reflect the degree of distortion of the power supply voltage waveform caused by harmonic and pulse clutter interference. The larger the effective value of the clutter voltage is relative to the effective value of the fundamental voltage, the higher the calculated voltage waveform distortion coefficient value, which represents the more serious power quality interference.

[0092] It can be seen that by performing Fourier transform on the voltage change data, the time-domain voltage signal is decomposed into fundamental voltage components and clutter voltage components. Then, the effective values ​​of the fundamental voltage components and clutter voltage components are calculated separately, and the voltage waveform distortion coefficient is determined. This can avoid misjudgment caused by instantaneous voltage fluctuations and reflect the interference effect of power quality on smoke alarms.

[0093] For example, the target interference coefficient is obtained by adjusting the reference interference coefficient based on the voltage waveform distortion coefficient. Specifically, the target interference coefficient can be calculated as follows: Target interference coefficient = Reference interference coefficient × (1 + Voltage waveform distortion coefficient); The target interference coefficient can be obtained by adjusting the reference interference coefficient based on the voltage waveform distortion coefficient in the manner described above.

[0094] As can be seen, the target power quality value is first determined by combining the first power quality value representing the duration of the peak voltage and the second power quality value representing the amplitude of the peak voltage impact. The reference interference coefficient corresponding to the target power quality is then matched. The voltage waveform distortion coefficient, which reflects the degree of waveform distortion caused by harmonic noise, is then calculated using voltage change data. This voltage waveform distortion coefficient is then used to correct the reference interference coefficient to output the final target interference coefficient. This avoids ignoring the interference caused by harmonic distortion corresponding to the power supply voltage, making the determination of the fault probability value closer to the real situation, thereby improving the fault location efficiency of the smoke alarm.

[0095] It should be explained that, in this embodiment, all peak voltages captured within a preset time period, i.e., m peak voltages, can be obtained first. For the occurrence time of each of the m peak voltages, the nearest zero-crossing point of the AC power supply voltage to that occurrence time is matched, thereby obtaining m independent phase differences corresponding to the m peak voltages. It is then determined whether the phase difference corresponding to each peak voltage falls within a preset zero-crossing interval. The number of peak voltages with phase differences within the preset zero-crossing interval is counted, and the ratio of this number to m is calculated to obtain the proportion of peak voltages that meet the conditions. When the proportion of peak voltages is greater than a preset proportion threshold, it is determined that the current voltage change data corresponds to a power grid interference event, and the interference coefficient corresponding to the power grid interference event is selected as the target interference coefficient. When the proportion of peak voltages is not greater than the preset proportion threshold, it is determined that it does not belong to a power grid interference event, and the target interference coefficient is determined according to the preset interference coefficient corresponding to the non-power grid interference event. Therefore, in this embodiment, the target interference coefficient can also be determined based on the phase distribution characteristics of the peak voltage relative to the zero-crossing point of the AC voltage.

[0096] For example, suppose 10 voltage spikes are captured within a preset time period. The time deviation between the occurrence of 9 of these voltage spikes and the zero-crossing point of the nearest AC power supply voltage is within ±1ms. The calculated percentage of voltage spikes meeting the criteria is 90%, which is higher than the preset percentage threshold of 80%. In this case, the disturbance is determined to be a power grid interference event, and the interference coefficient corresponding to the power grid interference event is selected as the target interference coefficient. If only 7 voltage spikes fall within the ±1ms range, corresponding to a percentage of 70%, which does not reach the preset percentage threshold, then it is determined not to be a power grid interference event, and the preset interference coefficient corresponding to non-power grid interference is used as the target interference coefficient.

[0097] The smoke alarm system also includes n fault indication devices, each corresponding to a smoke alarm. Please refer to [link / reference]. Figure 5 , Figure 5 This application provides a flowchart for providing fault indication, including but not limited to the following steps: S501: Generate k fault message messages corresponding to the k smoke detectors.

[0098] In this embodiment, each smoke alarm corresponds to a fault indication message. After determining that k smoke alarms corresponding to the k fault probability values ​​have malfunctioned, k fault indication messages need to be generated for each of the k smoke alarms. The fault indication message will clearly state the smoke alarm number, installation location, fault severity, cause of the problem, and simple maintenance suggestions, so that the indication device can quickly display it to the maintenance personnel.

[0099] It should be explained that the k fault prompts can be pushed to the operation and maintenance backend management terminal, the operation and maintenance personnel's mobile app, or SMS. The operation and maintenance personnel can view the corresponding prompts of the fault alarms in real time when they are in the computer room, on-site, or away from the site.

[0100] S502: Determine the k fault indication devices among the n fault indication devices that correspond to the k smoke alarms.

[0101] In this embodiment, please refer to Figure 6 , Figure 6 This is a layout diagram of a fault indication device provided in an embodiment of this application. In this embodiment, the fault indication device can be a fault light. The smoke alarm system includes a fault monitoring device and smoke alarms 1, 2, 3, and 4, as well as fault lights 1, 2, 3, and 4. Each smoke alarm corresponds to one fault light; smoke alarm 1 corresponds to fault light 1, smoke alarm 2 to fault light 2, smoke alarm 3 to fault light 3, and smoke alarm 4 to fault light 4. When the fault monitoring device determines that a smoke alarm is faulty and generates corresponding fault indication information, it can control the corresponding fault light to illuminate or flash. Maintenance personnel can quickly locate the faulty smoke alarm through the illuminated fault light on-site, improving the efficiency of locating faulty smoke alarms on-site.

[0102] For example, when smoke detector 1 and smoke detector 3 malfunction, the fault light 1 corresponding to smoke detector 1 and the fault light 2 corresponding to smoke detector 3 will light up. Maintenance personnel can quickly find the faulty smoke detector based on the lit fault lights, and thus quickly carry out the inspection or replacement of the faulty smoke detector.

[0103] When only k smoke detectors out of the n smoke detectors malfunction, it is necessary to identify the k fault indication devices that correspond to the k smoke detectors among the n fault indication devices to facilitate subsequent fault indication.

[0104] S503: The k fault indication devices indicate that the k smoke detectors have malfunctioned based on the k fault indication information.

[0105] In this embodiment, based on the k fault indication messages, it can be determined that the k smoke detectors have malfunctioned. At this time, the k fault indication devices corresponding to the k smoke detectors can be controlled to provide fault indication. Specifically, the corresponding indication mode can be switched according to the fault indication message. For high-risk faults, the system executes the indication logic of high-frequency flashing red light and voice broadcast of the device location and fault cause. For low-risk faults, the system executes the indication logic of constant yellow light and simple text display. By relying on lights, voice, and screen text, the system can intuitively show the on-site maintenance personnel that the corresponding smoke detector is faulty, making it easier for maintenance personnel to quickly locate the fault point and understand the relevant fault information.

[0106] In summary, implementing the embodiments of the present invention has the following beneficial effects: As can be seen, the fault location method described in this embodiment of the invention is applied to the fault monitoring device of a smoke alarm system. The smoke alarm system further includes n smoke alarms, where n is a positive integer. First, the fault monitoring device acquires the equipment operation monitoring data of each of the n smoke alarms within a preset time period, obtaining n sets of equipment operation monitoring data. Then, based on the n sets of equipment operation monitoring data, n fault probability values ​​corresponding to the n smoke alarms are determined. Next, k fault probability values ​​among the n fault probability values ​​that are greater than a preset fault probability threshold are determined. Finally, the k smoke alarms corresponding to the k fault probability values ​​are determined to have failed, thereby improving the fault location efficiency of the smoke alarm.

[0107] Please see Figure 7 , Figure 7 This is a schematic diagram of the structure of a fault location device provided in an embodiment of this application. The fault location device 700 is applied to the fault monitoring equipment of a smoke alarm system. The smoke alarm system also includes n smoke alarms, where n is a positive integer. The fault location device 700 includes: an acquisition unit 701 and a processing unit 702. The acquisition unit 701 is used to acquire the equipment operation monitoring data of each of the n smoke alarms within a preset time period, and obtain n sets of equipment operation monitoring data. The processing unit 702 is used to determine n fault probability values ​​corresponding to the n smoke alarms based on the n sets of equipment operation monitoring data; each smoke alarm corresponds to a fault probability value; the fault probability value is used to characterize the probability of the smoke alarm malfunctioning; Determine k fault probability values ​​from the n fault probability values ​​that are greater than a preset fault probability threshold; k is an integer less than or equal to n; The k smoke detectors corresponding to the k failure probability values ​​are determined to have malfunctioned.

[0108] In some possible implementations, when the first set of equipment operation monitoring data includes line transmission monitoring data and status reporting monitoring data, the first set of equipment operation monitoring data is the equipment operation monitoring data corresponding to the first smoke alarm, and the first smoke alarm is any one of the n smoke alarms; in determining the n fault probability values ​​corresponding to the n smoke alarms based on the n sets of equipment operation monitoring data, the processing unit 702 is specifically used for: Based on the line transmission monitoring data, the message transmission failure frequency and alarm linkage signal response duration of the first smoke alarm within the preset time period are determined. A reference fault probability value is determined based on the message transmission failure frequency and the alarm linkage signal response time. The on-time reporting rate of the first smoke alarm within the preset time period is determined based on the status reporting monitoring data. Determine the optimization factor corresponding to the on-time reporting rate of the status; The reference fault probability value is optimized based on the optimization factor to obtain the fault probability value corresponding to the first smoke alarm.

[0109] In some possible implementations, when the fault monitoring device includes a power quality acquisition module, the processing unit 702 is specifically used for determining a reference fault probability value based on the message transmission failure frequency and the alarm linkage signal response duration: Determine a first reference fault probability value corresponding to the message transmission failure frequency and a second reference fault probability value corresponding to the alarm linkage signal response time; A third reference fault probability value is determined based on the first reference fault probability value and the second reference fault probability value. The power quality acquisition module acquires voltage change data of the power supply voltage source that powers the first smoke alarm. The target interference coefficient is determined based on the voltage change data; The reference fault probability value is obtained by adjusting the third reference fault probability value based on the target interference coefficient.

[0110] In some possible implementations, in determining the target interference coefficient based on the voltage change data, the processing unit 702 is specifically configured to: The duration of the peak voltage and the maximum value of the peak voltage are determined based on the voltage change data; the duration of the peak voltage is the duration during which the voltage of the power supply voltage source exceeds a preset voltage threshold within the preset time period, and the maximum value of the peak voltage is the maximum voltage value of the power supply voltage source exceeding the preset voltage threshold within the preset time period; Determine the voltage difference between the maximum peak voltage and the preset voltage threshold; Determine a first power quality value corresponding to the duration of the peak voltage and a second power quality value corresponding to the voltage difference; The target interference coefficient is determined based on the first power quality value and the second power quality value.

[0111] In some possible implementations, in determining the target interference coefficient based on the first power quality value and the second power quality value, the processing unit 702 is specifically configured to: The target power quality value is determined based on the first power quality value and the second power quality value; Determine the interference coefficient corresponding to the target power quality value to obtain the reference interference coefficient; The voltage waveform distortion coefficient corresponding to the power supply voltage source is determined based on the voltage change data; the voltage waveform distortion coefficient is used to characterize the degree of distortion of the power supply voltage waveform corresponding to the power supply voltage source due to noise interference; The target interference coefficient is obtained by adjusting the reference interference coefficient based on the voltage waveform distortion coefficient.

[0112] In some possible implementations, the smoke alarm system further includes an interconnection communication device, which comprises n interconnection communication units, each interconnection communication unit being disposed within a smoke alarm. A first interconnection communication unit is disposed within the first smoke alarm, and the first interconnection communication unit is the interconnection communication unit among the n interconnection communication units corresponding to the first smoke alarm. The first interconnection communication unit includes: A level driving unit is used to output a preset alarm level compatible with the first smoke alarm. A frame encapsulation unit is used to encapsulate the initial device operation monitoring data corresponding to the first smoke alarm to obtain a reporting message; the reporting message includes the device identifier of the first smoke alarm. A cyclic redundancy check unit is used to filter out erroneous data in the reported message to obtain the target reported message; the monitoring data corresponding to the target reported message is the first group of equipment operation monitoring data. The pulse width coding modulation unit is used to modulate the target reporting message into a pulse width waveform, superimpose the pulse width waveform onto the preset alarm level, and transmit it to the fault monitoring device, so that the fault monitoring device can obtain the first set of equipment operation monitoring data.

[0113] In some possible implementations, The first interconnection communication device further includes: The power-on debounce unit is used to perform a debounce operation on the first smoke alarm based on a preset power-on debounce duration when the first smoke alarm is powered on, so as to avoid false alarms from the first smoke alarm. The wiring self-diagnostic unit is used to perform cross-comparison detection on the power supply live wire, power supply neutral wire and communication signal line connected to the first smoke alarm to identify the wiring misconnection fault corresponding to the first smoke alarm. When the first smoke alarm has the wiring misconnection fault, it will provide a prompt according to the preset wiring misconnection fault prompt operation.

[0114] Please see Figure 8 , Figure 8 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. The electronic device 800 is used as a fault monitoring device in a smoke alarm system, which further includes n smoke alarms, where n is a positive integer. Figure 8 As shown, the electronic device 800 includes a transceiver 801, a processor 802, and a memory 803. These are connected via a bus 804. The memory 803 stores computer programs and data, and the transceiver 801 can transmit data stored in the memory 803 to the processor 802. The program includes instructions for performing the following steps: Obtain the device operation monitoring data of each of the n smoke detectors within a preset time period to obtain n sets of device operation monitoring data; Based on the n sets of equipment operation monitoring data, n fault probability values ​​are determined for the n smoke alarms; each smoke alarm corresponds to one fault probability value; the fault probability value is used to characterize the probability of the smoke alarm malfunctioning; Determine k fault probability values ​​from the n fault probability values ​​that are greater than a preset fault probability threshold; k is an integer less than or equal to n; The k smoke detectors corresponding to the k failure probability values ​​are determined to have malfunctioned.

[0115] In some possible implementations, when the first set of equipment operation monitoring data includes line transmission monitoring data and status reporting monitoring data, the first set of equipment operation monitoring data is the equipment operation monitoring data corresponding to the first smoke alarm, and the first smoke alarm is any one of the n smoke alarms; in determining the n fault probability values ​​corresponding to the n smoke alarms based on the n sets of equipment operation monitoring data, the above procedure includes instructions for performing the following steps: Based on the line transmission monitoring data, the message transmission failure frequency and alarm linkage signal response duration of the first smoke alarm within the preset time period are determined. A reference fault probability value is determined based on the message transmission failure frequency and the alarm linkage signal response time. The on-time reporting rate of the first smoke alarm within the preset time period is determined based on the status reporting monitoring data. Determine the optimization factor corresponding to the on-time reporting rate of the status; The reference fault probability value is optimized based on the optimization factor to obtain the fault probability value corresponding to the first smoke alarm.

[0116] In some possible implementations, when the fault monitoring device includes a power quality acquisition module, the above procedure includes instructions for performing the following steps in determining a reference fault probability value based on the message transmission failure frequency and the alarm linkage signal response duration: Determine a first reference fault probability value corresponding to the message transmission failure frequency and a second reference fault probability value corresponding to the alarm linkage signal response time; A third reference fault probability value is determined based on the first reference fault probability value and the second reference fault probability value. The power quality acquisition module acquires voltage change data of the power supply voltage source that powers the first smoke alarm. The target interference coefficient is determined based on the voltage change data; The reference fault probability value is obtained by adjusting the third reference fault probability value based on the target interference coefficient.

[0117] In some possible implementations, the above procedure includes instructions for performing the following steps in determining the target interference coefficient based on the voltage change data: The duration of the peak voltage and the maximum value of the peak voltage are determined based on the voltage change data; the duration of the peak voltage is the duration during which the voltage of the power supply voltage source exceeds a preset voltage threshold within the preset time period, and the maximum value of the peak voltage is the maximum voltage value of the power supply voltage source exceeding the preset voltage threshold within the preset time period; Determine the voltage difference between the maximum peak voltage and the preset voltage threshold; Determine a first power quality value corresponding to the duration of the peak voltage and a second power quality value corresponding to the voltage difference; The target interference coefficient is determined based on the first power quality value and the second power quality value.

[0118] In some possible implementations, in determining the target interference coefficient based on the first power quality value and the second power quality value, the above procedure includes instructions for performing the following steps: The target power quality value is determined based on the first power quality value and the second power quality value; Determine the interference coefficient corresponding to the target power quality value to obtain the reference interference coefficient; The voltage waveform distortion coefficient corresponding to the power supply voltage source is determined based on the voltage change data; the voltage waveform distortion coefficient is used to characterize the degree of distortion of the power supply voltage waveform corresponding to the power supply voltage source due to noise interference; The target interference coefficient is obtained by adjusting the reference interference coefficient based on the voltage waveform distortion coefficient.

[0119] In some possible implementations, the smoke alarm system further includes an interconnection communication device, which comprises n interconnection communication units, each interconnection communication unit being disposed within a smoke alarm. A first interconnection communication unit is disposed within the first smoke alarm, and the first interconnection communication unit is the interconnection communication unit among the n interconnection communication units corresponding to the first smoke alarm. The first interconnection communication unit includes: A level driving unit is used to output a preset alarm level compatible with the first smoke alarm. A frame encapsulation unit is used to encapsulate the initial device operation monitoring data corresponding to the first smoke alarm to obtain a reporting message; the reporting message includes the device identifier of the first smoke alarm. A cyclic redundancy check unit is used to filter out erroneous data in the reported message to obtain the target reported message; the monitoring data corresponding to the target reported message is the first group of equipment operation monitoring data. The pulse width coding modulation unit is used to modulate the target reporting message into a pulse width waveform, superimpose the pulse width waveform onto the preset alarm level, and transmit it to the fault monitoring device, so that the fault monitoring device can obtain the first set of equipment operation monitoring data.

[0120] In some possible implementations, the first interconnect communication device further includes: The power-on debounce unit is used to perform a debounce operation on the first smoke alarm based on a preset power-on debounce duration when the first smoke alarm is powered on, so as to avoid false alarms from the first smoke alarm. The wiring self-diagnostic unit is used to perform cross-comparison detection on the power supply live wire, power supply neutral wire and communication signal line connected to the first smoke alarm to identify the wiring misconnection fault corresponding to the first smoke alarm. When the first smoke alarm has the wiring misconnection fault, it will provide a prompt according to the preset wiring misconnection fault prompt operation.

[0121] It should be understood that the electronic devices mentioned in this application may include smartphones (such as Android phones, iOS phones, Windows Phones, etc.), tablets, PDAs, laptops, mobile internet devices (MIDs) or wearable devices, servers, edge computing nodes, etc. The above-mentioned electronic devices are merely examples and not exhaustive, and include, but are not limited to, the electronic devices described above.

[0122] This application also provides a computer-readable storage medium storing a computer program that is executed by a processor to implement some or all of the steps of any of the methods described in the above method embodiments.

[0123] This application also provides a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program operable to cause a computer to perform some or all of the steps of any of the methods described in the above method embodiments.

[0124] It should be noted that, for the sake of simplicity, the aforementioned methods are described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are optional, and the actions and modules involved are not necessarily essential to this application.

[0125] In the above embodiments, the descriptions of each embodiment have their own emphasis. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0126] In the several embodiments provided in this application, it should be understood that the disclosed apparatus can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical or other forms.

[0127] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment, depending on actual needs.

[0128] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software program module.

[0129] If the integrated unit is implemented as a software program module and sold or used as an independent product, it can be stored in a computer-readable storage device (CMD). Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned memory includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0130] Those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage device, which may include: flash drive, read-only memory (ROM), random access memory (RAM), disk or optical disk, etc.

[0131] The embodiments of this application have been described in detail above. Specific examples have been used to illustrate the principles and implementation methods of this application. The above description of the embodiments is only for the purpose of helping to understand the method and core ideas of this application. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this application. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A fault location method, characterized in that, A fault monitoring device for a smoke alarm system, wherein the smoke alarm system further includes n smoke detectors, where n is a positive integer, and the method includes: Obtain the device operation monitoring data of each of the n smoke detectors within a preset time period to obtain n sets of device operation monitoring data; Based on the n sets of equipment operation monitoring data, n fault probability values ​​are determined for the n smoke alarms; each smoke alarm corresponds to one fault probability value; the fault probability value is used to characterize the probability of the smoke alarm malfunctioning; Determine k fault probability values ​​from the n fault probability values ​​that are greater than a preset fault probability threshold; k is an integer less than or equal to n; Determine that k smoke detectors corresponding to the k fault probability values ​​have malfunctioned; Wherein, when the first set of equipment operation monitoring data includes line transmission monitoring data and status reporting monitoring data, the first set of equipment operation monitoring data is the equipment operation monitoring data corresponding to the first smoke alarm, and the first smoke alarm is any one of the n smoke alarms; the step of determining the n fault probability values ​​corresponding to the n smoke alarms based on the n sets of equipment operation monitoring data includes: Based on the line transmission monitoring data, the message transmission failure frequency and alarm linkage signal response duration of the first smoke alarm within the preset time period are determined. A reference fault probability value is determined based on the message transmission failure frequency and the alarm linkage signal response time. The on-time reporting rate of the first smoke alarm within the preset time period is determined based on the status reporting monitoring data. Determine the optimization factor corresponding to the on-time reporting rate of the status; The reference fault probability value is optimized based on the optimization factor to obtain the fault probability value corresponding to the first smoke alarm.

2. The method as described in claim 1, characterized in that, When the fault monitoring device includes a power quality acquisition module, determining the reference fault probability value based on the message transmission failure frequency and the alarm linkage signal response duration includes: Determine a first reference fault probability value corresponding to the message transmission failure frequency and a second reference fault probability value corresponding to the alarm linkage signal response time; A third reference fault probability value is determined based on the first reference fault probability value and the second reference fault probability value. The power quality acquisition module acquires voltage change data of the power supply voltage source that powers the first smoke alarm. The target interference coefficient is determined based on the voltage change data; The reference fault probability value is obtained by adjusting the third reference fault probability value based on the target interference coefficient.

3. The method as described in claim 2, characterized in that, Determining the target interference coefficient based on the voltage change data includes: The duration of the peak voltage and the maximum value of the peak voltage are determined based on the voltage change data; the duration of the peak voltage is the duration during which the voltage of the power supply voltage source exceeds a preset voltage threshold within the preset time period, and the maximum value of the peak voltage is the maximum voltage value of the power supply voltage source exceeding the preset voltage threshold within the preset time period; Determine the voltage difference between the maximum peak voltage and the preset voltage threshold; Determine a first power quality value corresponding to the duration of the peak voltage and a second power quality value corresponding to the voltage difference; The target interference coefficient is determined based on the first power quality value and the second power quality value.

4. The method as described in claim 3, characterized in that, The smoke alarm system further includes n fault indication devices, each corresponding to a smoke alarm. After determining that the k smoke alarms corresponding to the k fault probability values ​​have malfunctioned, the method further includes: Generate k fault message messages corresponding to the k smoke detectors; each smoke detector corresponds to one fault message message. Identify the k fault indication devices among the n fault indication devices that correspond to the k smoke detectors; The k fault indication devices notify the k smoke detectors that a malfunction has occurred based on the k fault indication information.

5. The method according to any one of claims 2-4, characterized in that, The smoke alarm system further includes an interconnection communication device, which comprises n interconnection communication units, each interconnection communication unit being installed within a smoke alarm. A first interconnection communication unit is installed within the first smoke alarm, and this first interconnection communication unit is the interconnection communication unit among the n interconnection communication units that corresponds to the first smoke alarm. The first interconnection communication unit includes: A level driving unit is used to output a preset alarm level compatible with the first smoke alarm. A frame encapsulation unit is used to encapsulate the initial device operation monitoring data corresponding to the first smoke alarm to obtain a reporting message; the reporting message includes the device identifier of the first smoke alarm. A cyclic redundancy check unit is used to filter out erroneous data in the reported message to obtain the target reported message; the monitoring data corresponding to the target reported message is the first group of equipment operation monitoring data. The pulse width coding modulation unit is used to modulate the target reporting message into a pulse width waveform, superimpose the pulse width waveform onto the preset alarm level, and transmit it to the fault monitoring device, so that the fault monitoring device can obtain the first set of equipment operation monitoring data.

6. The method as described in claim 5, characterized in that, The first interconnection communication device further includes: The power-on de-shaking unit is used to perform a de-shaking operation on the first smoke alarm based on a preset power-on de-shaking duration when the first smoke alarm is powered on, so as to avoid false alarms from the first smoke alarm. The wiring self-diagnostic unit is used to perform cross-comparison detection on the power supply live wire, power supply neutral wire and communication signal line connected to the first smoke alarm to identify the wiring misconnection fault corresponding to the first smoke alarm. When the first smoke alarm has the wiring misconnection fault, it will provide a prompt according to the preset wiring misconnection fault prompt operation.

7. A fault location device, characterized in that, A fault monitoring device for a smoke alarm system, wherein the smoke alarm system further includes n smoke alarms, where n is a positive integer, and the device includes: an acquisition unit and a processing unit; The acquisition unit is used to acquire the equipment operation monitoring data of each of the n smoke alarms within a preset time period through the fault monitoring device, and obtain n sets of equipment operation monitoring data. The processing unit is used to determine n fault probability values ​​corresponding to the n smoke alarms based on the n sets of equipment operation monitoring data; each smoke alarm corresponds to a fault probability value; the fault probability value is used to characterize the probability of the smoke alarm malfunctioning; Determine k fault probability values ​​from the n fault probability values ​​that are greater than a preset fault probability threshold; k is an integer less than or equal to n; Determine that k smoke detectors corresponding to the k fault probability values ​​have malfunctioned; Wherein, when the first set of equipment operation monitoring data includes line transmission monitoring data and status reporting monitoring data, the first set of equipment operation monitoring data is the equipment operation monitoring data corresponding to the first smoke alarm, and the first smoke alarm is any one of the n smoke alarms; the step of determining the n fault probability values ​​corresponding to the n smoke alarms based on the n sets of equipment operation monitoring data includes: Based on the line transmission monitoring data, the message transmission failure frequency and alarm linkage signal response duration of the first smoke alarm within the preset time period are determined. A reference fault probability value is determined based on the message transmission failure frequency and the alarm linkage signal response time. The on-time reporting rate of the first smoke alarm within the preset time period is determined based on the status reporting monitoring data. Determine the optimization factor corresponding to the on-time reporting rate of the status; The reference fault probability value is optimized based on the optimization factor to obtain the fault probability value corresponding to the first smoke alarm.

8. An electronic device, characterized in that, The method includes a processor, a memory, a communication interface, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the processor, and the one or more programs include instructions for performing the steps of the method according to any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that is executed by a processor to implement the method as described in any one of claims 1-6.

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