373 results about "Alarm state" patented technology

The invention discloses a time-phased intelligent pressure regulation management method and system for secondary water supply, and belongs to the technical field of water supply management, and the method specifically comprises the steps: dividing a day into a water consumption peak period and a water consumption low period based on historical water consumption flow data, and determining the starting and ending time nodes of each time period; through hydraulic calculation and actual water supply pressure monitoring, a pressure control point at the tail end of the water supply system is locked, and water supply pressure data of the point are collected in real time; in the water consumption peak period, a peak pressurization control strategy is executed; in the water consumption low-peak period, analysis is conducted according to historical water supply pressure data of a tail end pressure control point, and a low-peak period pressure safety threshold value is set; a pressure instruction is sent to a control system according to the threshold value, and water supply equipment is controlled to output pressure according to the threshold value; the water supply pressure of a tail end pressure control point is monitored in real time, and when the pressure is lower than a low-peak-period pressure safety threshold value, pre-alarm is triggered, and pressure changes are continuously recorded; and if the pre-alarm state is not finished continuously, switching to a peak-period peak pressurization control strategy.

The invention relates to an intelligent scheduling method and device for communication network resources, equipment and a medium. The method comprises the following steps: performing IP packet header analysis on a service data packet to obtain an initial service priority identifier, and performing adjustment in combination with a preset priority rule, an equipment alarm state and a network congestion rate to generate a dynamic service label; based on the dynamic service label, the real-time link state and the energy consumption coefficient, generating a resource allocation strategy and a path scoring weight parameter through a preset deep reinforcement learning network; and calculating a path score based on the resource allocation strategy and the path score weight parameter, generating a path mapping table, generating a port suppression instruction based on the dynamic service label and the resource allocation strategy, and extracting a base station power regulation instruction. According to the method, the dynamic adaptability, the resource utilization rate and the energy consumption management and control capability of communication network resource scheduling are improved by means of dynamically adjusting the service priority, comprehensively modeling a resource allocation strategy and the like, and the transmission guarantee level of high-priority services is enhanced.

The embodiment of the invention provides an addressing-to-non-addressing device and an alarm system wherein the addressing-to-non-addressing device comprises: a non-addressing node state monitoring module, which is connected with a non-addressing node and is used for monitoring the voltage in a loop where the non-addressing node is located; the non-addressing node is used for detecting environmental parameters of the target area, and the non-addressing node is in an alarm state under the condition that the environmental parameters are abnormal; the controller is connected with the non-addressing node state monitoring module, and the controller is further configured to be connected with an addressing host and used for receiving the voltage detected by the non-addressing node state monitoring module, determining fault information based on the voltage and sending the fault information to the addressing host. According to the invention, the problem that the non-addressing node cannot communicate with the addressing host in the prior art is solved, and the effect that the non-addressing node communicates with the addressing host is achieved.

The invention belongs to the technical field of new energy automobile batteries, and provides a vehicle battery abnormity processing method and device, a storage medium and a vehicle, and the method comprises the steps: if a current battery is in a to-be-alarmed state, determining that a current condition accords with a preset alarm condition of vehicle battery thermal runaway alarm through a vehicle battery abnormity determination strategy, if so, cutting off the current battery high voltage and generating thermal runaway alarm information. Through the processing method, the current battery high voltage is cut off and the thermal runaway alarm information is generated only on the premise that the current condition meets the preset alarm condition of the vehicle battery thermal runaway alarm; therefore, the accuracy of vehicle battery abnormity alarm is greatly improved, the thermal runaway alarm information can be quickly, timely and automatically generated, and the safety of vehicle driving is greatly improved.

The invention belongs to the technical field of fire-fighting monitoring, and particularly relates to a multi-source intelligent fire-fighting monitoring and response method, system and terminal based on hierarchical linkage. The method comprises the following steps: acquiring environmental parameters such as temperature and smoke collected by monitoring equipment in a plurality of target areas, and constructing first data information; a judgment model is generated based on the temperature and smoke change trend, and the regional state is judged to be safe or alarm; if the state is an alarm state, determining a disaster category in combination with a threshold comparison result; executing alarm or fire extinguishing response according to the disaster category; meanwhile, identifying an associated region related to the target region, determining a linkage level according to a preset rule, and executing a hierarchical response; and finally, generating a checking result according to a response effect, and dynamically optimizing the judgment model and the response strategy. According to the system, multi-source information fusion, intelligent fire identification and multi-region collaborative response are realized, and the timeliness and accuracy of intelligent fire fighting are improved.

The invention discloses a tunnel, bridge and culvert water level detection and alarm system and method based on deep learning, and the method comprises the following steps: S1, collecting an image and a capacitance water level signal at the lowest point of a tunnel or an easy water accumulation region, and generating standardized multi-source data; s2, inputting the image into a SegmentAnything model, extracting a water body mask, and calculating an image water level value in combination with scale mapping; s3, carrying out confidence weighted fusion on the image water level and the capacitance signal to obtain a fused water level value; s4, constructing a fused water level time sequence, constructing an SCI Net model, and outputting a predicted water level sequence; s5, generating an alarm label according to the fused water level and the prediction result; s6, LED display and acousto-optic response are controlled according to the alarm label, and an early warning prompt is started when a serious alarm is given; s7, capturing an image in an early warning or serious alarm state, and generating an alarm data packet; and S8, uploading to an urban water level monitoring platform through the Internet of Things module. According to the invention, intelligent identification and remote early warning of the ponding state of the tunnel bridge and culvert are realized.

A method of detecting anomalies using alarm data from a manufacturing network for manufacturing a product in batches includes obtaining alarm data, the alarm data indicates timing alarm state information of each alarm among one or more types of a plurality of alarms among a plurality of types of alarms during a plurality of batches. Each type of alarm is indicative of a different type of problem. The plurality of alarms includes a first alarm and a second alarm. For each batch, a probability that the second alarm will occur within a specified period of time after the first alarm is calculated based on the alarm data. A cumulative sum (CUSUM) of average deviations of probabilities calculated for each batch is stepwise calculated, and a batch having a maximum absolute value of the CUSUM is identified as a point-of-change batch exhibiting a potential anomaly indicative of a problem in the manufacturing network that requires investigation or repair.

The invention provides a liquid chromatograph state monitoring and predictive maintenance method and a liquid chromatograph state monitoring and predictive maintenance system, and relates to the technical field of data processing. Liquid chromatograph sensor data (continuous parameters such as flow, temperature, pressure and the like) and log data (discrete information such as alarm state, equipment event and the like) are subjected to joint modeling; and data dimension reduction is carried out based on the geometric similarity of the data points, so that the local structure and global information of the data of the liquid chromatograph are kept, and meanwhile, information loss in the dimension reduction process is reduced. The state monitoring model is further utilized for data processing, the context sensing ability of the model is improved, when abnormity or faults occur, multiple factors can be comprehensively considered for accurate diagnosis, and higher accuracy and reliability are shown when complex state changes of the liquid chromatograph are monitored.

A method and system for detecting a denial of service (DOS) attack when packets used in the DOS attack are user datagram protocol (UDP) packets, are disclosed. The method includes obtaining values from an application header of a UDP packet; and when, based on use of at least one modified probabilistic Bloom filter (PMBF) for a destination to which the UDP packet indicates that it is destined, the obtained values are not values expected to be found in a UDP packet destined for the destination: increasing an uncommon per sample (ups) estimate for the PMBF; and when the increased uncommon per sample estimate is greater than an upper ups threshold: setting an alarm state to on; suspending update of the PMBF counters; and initiating a mitigation action at least with respect to the UDP packet.

The invention discloses a multi-axial mechanical accelerometer and a measuring method, and relates to the technical field of mechanical accelerometer equipment.The multi-axial mechanical accelerometer comprises a dome shell, a touch type alarm is installed in the dome shell, a transverse shaft is installed in the dome shell in the radial line direction of the dome shell, and the transverse shaft is sleeved with a conical sleeve; the conical sleeve is in sliding fit with the transverse rod, and the transverse shaft is sleeved with a first reset spring used for driving the conical sleeve to be close to the touch type alarm. The first base is installed at the bottom of the dome shell, a limiting assembly used for limiting the conical sleeve to move in the radial line direction is installed in the bottom of the first base, and the limiting assembly can move in the axis direction in the first base; when the multi-axial mechanical accelerometer works, acceleration signals in the axial direction and acceleration signals in the axial direction of other intersecting coordinate systems are responded, acceleration values in the axial direction of the multi-axial mechanical accelerometer are measured, an over-limit alarm state is indicated, and an alarm signal is output.

The invention discloses an operation alarm method and system for a power system, and belongs to the technical field of power system monitoring, and the method comprises the steps: deploying a distributed intelligent sensing network to collect data in a layered manner, and extracting basic physical characteristics; semantic annotation and hierarchical credibility evaluation are carried out on the basic physical features to generate a credible physical feature set; constructing a semantic causal graph and optimizing an edge weight through disturbance simulation to extract a dynamic risk factor; constructing a layered state vector and a dynamic health threshold vector, and comparing the layered state vector and the dynamic health threshold vector to generate an operation alarm state; and executing attribution analysis according to the operation alarm state to generate a threshold calibration signal for feedback. According to the method, the technical scheme of combining multi-source data fusion, hierarchical credibility evaluation, causal risk modeling and dynamic threshold adaptive calibration is adopted, so that accurate identification and prospective early warning of potential risks of the power system can be realized, and the accuracy and adaptive capability of alarm decision making are improved.

The invention discloses an acceleration tube full-process automatic reliability test system and device, and relates to the technical field of high-power microwave device testing, and the system specifically comprises the following modules: a control test module, a hardware control module, an acquisition processing module, a business logic module, a data persistence module, and a user performance module. Writing and executing an automatic reliability test script of the acceleration tube; receiving and executing a hardware control instruction, and uploading an original analog / digital signal of the equipment; the communication module communicates with equipment in the hardware control module, converts an original analog / digital signal into a digital signal which can be processed by a C # program, and carries out filtering, unit conversion and validity verification on the digital signal; an over-limit alarm function is provided, and the structured test data is sent to the data persistence layer; storing all test related data through a relational database; test parameter configuration, real-time monitoring, alarm states, data records and dose rate curves are provided based on a graphical user interface.

The invention provides a Gaussian pollution diffusion source intensity quantification method and system based on adaptive parameter correction, and relates to the technical field of environmental monitoring, and the method comprises the following steps: S1, obtaining monitoring data at a moment K through a fixed sensor in a target area subjected to grid processing; s2, performing early warning judgment on the station state of the fixed sensor according to the monitoring data, when the station state is judged to be an alarm state, recording the station position of the fixed sensor as an alarm point position, performing range screening around the alarm point position to obtain a plurality of point positions to be estimated, and turning to the step S3; s3, obtaining monitoring data of the alarm point location before the moment K, and performing Gaussian simulation diffusion according to the monitoring data of the moment K corresponding to the alarm point location, the monitoring data before the moment K, the site location and the plurality of to-be-estimated point locations; and S4, according to the monitoring data of all the fixed sensors and the pollutant diffusion concentration at the moment K corresponding to the alarm point location, the diffusion parameter is corrected.

The invention provides a heat tracing system temperature monitoring and early warning method and system, and belongs to the technical field of temperature monitoring and early warning, and the method comprises the steps: 1, obtaining a plurality of field nodes of a heat tracing system, deploying a preset collection device on each field node, and carrying out the real-time collection of the heat tracing temperature of each field node; 2, packaging the collected real-time temperature data, and sending the packaged real-time temperature data to a corresponding team receiving device; 3, the received real-time temperature data are processed and transmitted to a cloud platform; 4, acquiring historical temperature data of each field node in the heat tracing system, determining a plurality of temperature judgment threshold values, and then sending out an alarm signal; and 5, constructing a multi-level management view based on the real-time temperature data of all the field nodes and the alarm state, and then obtaining a temperature monitoring result, thereby effectively improving the temperature monitoring efficiency and early warning timeliness of the heat tracing system, and remarkably enhancing the stability and safety of the system.

Aspects of the disclosure are directed to voltage sensing for safety-critical applications. In accordance with one aspect, the disclosure includes a multi-phase ring oscillator (RO) configured to operate in a first voltage domain; a frequency counter coupled to the multi-phase RO, the frequency counter configured to accumulate a plurality of phase cycles from the multi-phase RO over a time duration to generate a digital count word; an alarm processor coupled to the frequency counter, the alarm processor configured to receive an alarm state signal from the frequency counter; and a heartbeat detector coupled to the multi-phase RO, the heartbeat detector configured to operate in a second voltage domain and configured to detect a periodic recurrence of a heartbeat pulse to determine an integrity of the sensor function as a whole and alarm state signal in particular.

The invention provides an alarm method and system based on an intelligent door lock and a storage medium. According to induction data received by a first intelligent door lock, first alarm information is sent to a first user APP, and meanwhile the alarm information is broadcasted to a second intelligent door lock; the second intelligent door lock receives the alarm information, gives an alarm to the second intelligent door lock according to the spatial position relation between the second intelligent door lock and the first intelligent door lock and the alarm time interval, and sends second alarm information to a second user APP corresponding to the second intelligent door lock; and according to the living attributes of the first intelligent door lock and the second intelligent door lock, if the first intelligent door lock and / or the second intelligent door lock are / is in an alarm state within a preset duration, and unlocking of the resident is not detected, the first intelligent door lock and / or the second intelligent door lock give an alarm to the outside based on the door lock management platform. Fire-fighting alarm can be performed at the first time through linkage alarm by the intelligent door lock; meanwhile, safety tracking is carried out according to the resident condition.

The present invention relates to the technical field of energy network regulation and control. Disclosed is a user-side integrated energy network coordination control method and system. The method comprises: acquiring energy supply and consumption data of each loop, calculating an actually measured value of a carbon emission responsibility factor of each node, and calculating an actual value of the total carbon emission amount of a user; comparing the actual value of the total carbon emission amount of the user with a limit value of the total carbon emission amount of the user, and when the total carbon emission amount of the user reaches an alarm state, sending warning information to the user; on the basis of predicted data of energy supply and consumption at time t, calculating a predicted value of the carbon emission responsibility factor of each node at time t, and obtaining a carbon emission high-crossing limit value of each node; and comparing the actually measured value of the carbon emission responsibility factor, the predicted value of the carbon emission responsibility factor and the carbon emission high-crossing limit value, and on the basis of the comparison result, configuring an operation mode of each node or issuing an execution instruction to an instruction execution device of each node loop. The present invention ensures that the total carbon emission amount of a user-side integrated energy network meets the limit requirements.

The invention discloses a sensor damage detection method and system, and belongs to the technical field of damage detection. The system comprises a data acquisition module, an anomaly analysis module, a damage detection module and an intelligent early warning module. The data acquisition module is used for acquiring a running log and acquiring vibration acceleration in three-axis directions through a sensor module mounted on mechanical equipment; the anomaly analysis module analyzes parameter records of the sensor modules in the running log, calculates influence coefficients among the sensor modules, analyzes whether influence relations exist or not, establishes a relation network and screens out suspicious sensor modules; the damage detection module calculates an abnormal index through the vibration acceleration of the suspicious sensor module, judges whether to enter an alarm state or not according to the change of the abnormal index, and carries out rapid dredging and abnormal alarm on data in the sensor module in the alarm state; the intelligent early warning module displays the data information uploaded by the alarm device in real time through a large visual screen, and notifies a manager of the occurrence of an abnormal event.

Determining clusters of similar regularly occurring time periods for alarm data. Detect, for regularly occurring time periods in the alarm data, a change of alarm state and its associated time stamp. Analyze the alarm data along a timeline to detect at least an overlapping period of time for pairs of the plurality of regularly occurring time periods. Determine at least one aggregate similarity value for regularly occurring time periods. Determine a similarity matrix based on the at least one determined aggregate similarity value for each pair of regularly occurring time periods. Determine one or more clusters of similar regularly occurring time periods based upon analysis of the determined similarity matrix between the plurality of regularly occurring time periods. Provide a tangible output identifying the determined one or more clusters of similar regularly occurring time periods for the plurality of regularly occurring time periods.

The invention provides a three-level alarm identification method and device for an automobile battery. The method comprises the following steps: firstly, receiving real-time signal data uploaded by a target vehicle; then, performing data cleaning on the real-time signal data to obtain an input parameter set; finally, the input parameter set is input into a third-level alarm recognition model, whether the battery of the target vehicle is in a third-level alarm state or not is judged through the third-level alarm recognition model, and the third-level alarm recognition model is a bidirectional long-short-term memory structure sequence model obtained through pre-training. Therefore, the three-level alarm identification model is obtained by pre-training the bidirectional long and short time memory structure sequence model, and the time sequence characteristics of the signal data before and after the alarm moment can be considered, so that the three-level alarm identification model can accurately and effectively identify whether the vehicle battery is in the three-level alarm state. Therefore, the fault of the vehicle battery can be analyzed and processed in time, and the use risk of the new energy battery is reduced.

The invention relates to the technical field of urban intelligent traffic, in particular to a congestion alarm method based on visual large model secondary verification, which comprises the following steps: periodically acquiring traffic parameters of each road section of a target road and a congestion alarm state of a previous period; according to the traffic parameters and the congestion alarm state of the previous period, performing preliminary congestion state identification, and generating a congestion alarm alternative set; based on historical false alarm information and historical disposal information of each road section of the target road, screening and priority ranking are carried out on the congestion alarm alternative set, and a congestion alarm to-be-analyzed list after priority ranking is generated; acquiring a real-time video stream corresponding to each road section in the congestion alarm to-be-analyzed list, inputting the real-time video streams into a preset visual large model, and acquiring a false alarm set and a final congestion alarm set; and performing congestion alarm according to the final congestion alarm set and a preset alarm rule. According to the invention, the accuracy and reliability of congestion alarm are obviously improved.

The invention discloses a user-side integrated energy network coordination control method and system, and relates to the technical field of energy network regulation and control, and the method comprises the steps: obtaining the energy supply and consumption data of each loop, calculating the measured value of a carbon emission responsibility factor of each node, and calculating the actual value of the total carbon emission of a user; comparing the actual value of the total carbon emission amount of the user with the limiting value of the total carbon emission amount of the user, and sending warning information to the user when the total carbon emission amount of the user reaches an alarm state; calculating a carbon emission responsibility factor predicted value of each node at the t moment through the predicted data of energy supply and consumption at the t moment, and obtaining a carbon emission high-pass limit value of each node; and the instruction execution device is used for comparing the carbon emission responsibility factor measured value, the carbon emission responsibility factor predicted value and the carbon emission high-crossing limit value, and setting the operation mode of each node or issuing an execution instruction to each node loop according to a comparison result. The method ensures that the total carbon emission of the user-side integrated energy network meets the limit value requirement.

The invention discloses a supply chain auditing risk monitoring and early warning system based on artificial intelligence, which relates to the technical field of supply chain auditing and comprises the following steps of: packaging a multi-service system receipt change into an event packet containing a source identifier, an event type, a service primary key set, event time, lake entering time and an aperture version; idempotent duplicate removal is additionally written into an event account book, and an alarm entity is generated; when an alarm is about to be bound, a consistent slice definition is generated, a pointer type snapshot or a materialized snapshot and a seal object are formed, a verification value is calculated in a normalized and serialized mode, and two-stage submission binding is carried out to form an evidence packet; the evidence integrity is calculated according to a risk type template, and the double-threshold alarm gate state machine migrates an alarm state and distributes an evidence repair task; and performing deterministic playback according to the evidence packet and outputting a difference attribution report for closed-loop processing, thereby realizing reproducible and verifiable alarm, supporting third-party verification, reducing false alarm outgoing, and shortening re-checking positioning time and proof.

The invention relates to the technical field of lamp bead active heat dissipation, and discloses an LED lamp bead active heat dissipation system and method, and the method comprises the steps: injecting a micro-current pulse into a PN junction of an LED chip through a constant current source, collecting a forward voltage drop sampling value, and collecting a substrate temperature sampling value; calculating a junction temperature value based on the forward voltage drop sampling value, and calculating a junction-to-case temperature difference value and a substrate temperature rise rate value; setting an early-warning state identifier when the junction-to-case temperature difference value exceeds an early-warning threshold value and the duration meets a preset duration, setting an alarm state identifier when the junction-to-case temperature difference value exceeds an alarm threshold value, and shielding thermal runaway detection when the substrate temperature rise rate value exceeds an environment thermal shock threshold value and the junction-to-case temperature difference value is smaller than an environment exclusion threshold value; when the state identification is the normal state identification, calculating a first compensation current value; and when the state identification is the early warning state identification, a second compensation current value is calculated, and when the state identification is the alarm state identification, an alarm current limiting value is calculated, so that the working stability and long-term reliability of the LED in a wide temperature range are ensured.

The invention discloses a synchronization method and system based on a state change log, and the method comprises the steps: a main device obtains an alarm state change event, records the state change log, and adds the state change log into a log queue; the slave device initiates a synchronization request to the master device, and the master device judges the consistency of the configuration version based on the synchronization request; if the configuration versions are consistent, the master device performs incremental synchronization condition judgment based on the synchronization request; if yes, the master device sends incremental update data to the slave device; otherwise, the master device sends the total update data to the slave device; the slave device performs incremental synchronization or full synchronization according to the received update data. Under the condition of the existing redundancy deployment master-slave mode, the log of the alarm state change is used as the basis of the alarm state synchronization, and the incremental synchronization and the full-amount synchronization between the master device and the slave device are judged, so that the data transmission pressure caused by frequently adopting the full-amount synchronization is effectively reduced, and the data transmission efficiency is improved. And the logic complexity of data synchronization is reduced.

The invention provides an open-pit mine landslide monitoring device, which comprises a base, and is characterized in that the base is provided with mounting cavities communicated with each other and a mounting port located in the front side wall of the base; the pressure sensor is arranged in the mounting cavity; the triggering part comprises a first triggering end and a second triggering end which are movably arranged at the mounting opening in a penetrating mode and are oppositely arranged, the first triggering end is located on the outer side of the base, and the second triggering end is located in the mounting cavity, located on the front side of the pressure sensor and connected with or separated from the pressure sensor in an abutting mode; the first elastic part is arranged between the base and the triggering part and is used for applying an acting force away from the base to the triggering part; an alarm unit; the control system is electrically connected with the pressure sensor and the alarm part, the alarm part is in an alarm state or a non-alarm state according to pressure information received by the control system, and when the pressure value exceeds a pressure threshold value and the duration exceeds a time threshold value, the alarm part gives an alarm. According to the scheme, the alarm reliability of the strip mine landslide monitoring device is improved.

The utility model discloses a crane motor temperature alarm circuit, which relates to the technical field of motor temperature alarm, and comprises a temperature detection module for detecting the temperature of a crane motor and calculating the temperature change degree in a short time when the temperature reaches a set temperature, when the temperature difference is larger than a set temperature difference threshold value, there is an over-temperature risk, at the moment, the alarm control module carries out light alarm, the over-temperature detection module carries out over-temperature detection, and when the temperature is over-temperature, the alarm control module carries out sound alarm. When the crane motor is over-temperature and the temperature difference is larger than a set temperature difference threshold value, sound alarm is maintained, the alarm control module transmits the alarm state to the monitoring terminal in a wireless mode, the crane motor temperature alarm circuit can conduct over-temperature alarm in advance, the over-temperature risk is reduced, alarm with different effects can be conducted according to different temperature states, and the safety of the crane motor is improved. The alarm effect is improved.

The invention provides a fire alarm prediction method and device based on a high-order Markov chain. The method provided by the invention comprises the following steps: converting a subsequence in historical state sequence data of the fire-fighting equipment into data to form a first state sequence of the fire-fighting equipment; determining a state space based on the first state sequence of the fire-fighting equipment; determining the order of a high-order Markov chain model based on the length of the historical state sequence data, and constructing the high-order Markov chain model based on the order and the state transition probability matrix; solving the target function under the constraint condition based on a linear programming solver to obtain model parameters of a Markov chain model, and obtaining an optimized Markov chain model based on a solving result; and predicting a fire alarm state in the first time period based on the high-order Markov chain model. According to the fire alarm prediction method and device based on the high-order Markov chain provided by the invention, rapid analysis of a fuzzy system state is realized through short-term data so as to predict a short-term fire risk.

Techniques are described for monitoring the health of services in a computing environment such as a data center. More particularly, the present disclosure describes techniques for monitoring the health and availability of capabilities in a computing environment such as a data center by enabling alarms to be associated with the capabilities. A capability refers to a set of resources in a data center. By providing the ability to associate an alarm with a capability, the health or availability of the associated capability can be monitored or ascertained by tracking the state of the alarm associated with the capability. For example, if the alarm associated with a particular capability is triggered, it may indicate that the particular capability and the one or more resources corresponding to the particular capability are not in a healthy state. Accordingly, by monitoring alarms associated with capabilities, the health of the associated capabilities can be ascertained.

The invention relates to the technical field of fire sensing, and discloses an electrical fire state sensing system and method for a low-voltage distribution line, and the method comprises the steps: setting a first monitoring point at a wire inlet end of a distribution loop, setting a second monitoring point at a load access end, setting a differential protection region, and calculating a first on-resistance; performing moving average processing on the first on-resistance to obtain a second on-resistance, calculating a first reference on-resistance according to the second on-resistance, and performing temperature correction on the first reference on-resistance to obtain a second reference on-resistance; according to the method, the on-resistance deviation rate, the on-resistance growth rate and the on-resistance fluctuation coefficient are calculated, whether the on-resistance is in an early warning state, an alarm state or a dangerous state is judged, the on-resistance of the section is calculated in real time according to the ratio of the differential voltage drop to the current, and the technical problem that a fault section cannot be accurately positioned through traditional whole-line monitoring is solved.