CN117921139A - Welding machine operation monitoring device, method and system based on power grid end - Google Patents
Welding machine operation monitoring device, method and system based on power grid end Download PDFInfo
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Abstract
The invention relates to the technical field of electric power monitoring, in particular to a welding machine operation monitoring device, method and system based on a power grid end, which are arranged at a plurality of set positions on the low-voltage side of a power grid distribution transformer, can monitor whether the load carried by the distribution transformer has the electric welding machine fire operation or not in a non-interference manner, if so, transmit monitoring results and position information to a server or a cloud platform through the Internet of things, compare the monitoring results and the position information with electric welding machine fire operation permission information stored in the server, and if no fire operation application permission exists, send out an alarm and position information. Not only can effectively prevent the occurrence of fire disasters of the electric welding machine, but also can improve the investigation work efficiency of fire accidents.
Description
Technical Field
The invention relates to the technical field of power monitoring, in particular to a welding machine operation monitoring device, method and system based on a power grid end.
Background
The statements in this section merely provide background information related to the present disclosure and may not necessarily constitute prior art.
A welder (electric welding machine) is one of the most commonly used electromechanical devices in many industries such as industrial manufacturing, and melts solder and a material to be welded by using a high-temperature arc generated when positive and negative electrodes are instantaneously short-circuited. The electric welding machine can generate high temperature during operation and is accompanied by a large amount of spark scrap iron to splash, and fire is easy to trigger, so that the electric welding machine has potential danger.
Existing welding machine monitoring technologies generally monitor state information of a welding machine at a production construction site, such as video monitoring, environmental information monitoring, welding machine self-voltage current monitoring and the like. But such monitoring information cannot grasp the potential risks existing in the operation of the electric welding machine.
Disclosure of Invention
In order to solve the technical problems in the background art, the invention provides a welding machine operation monitoring device, method and system based on a power grid end, which can monitor whether the load carried by a distribution transformer of a power grid has the operation of an electric welding machine on line through a plurality of set positions arranged on the low-voltage side of the distribution transformer of the power grid, if so, the monitoring result and the position information are transmitted to a fire control server or a cloud platform through the Internet of things, and are compared with the operation permission information of the electric welding machine stored in the server, and if no operation application permission of the electric welding machine exists, an alarm and the position information are sent out. Not only can effectively prevent the occurrence of fire disasters of the electric welding machine, but also can improve the investigation work efficiency of fire accidents.
A first aspect of the present invention provides a power grid-side-based welder operation monitoring device, comprising:
The current and voltage sensing unit acquires current and voltage data of a set monitoring point, performs preprocessing on the received data through the signal conditioning unit, converts the preprocessed analog signal into a digital signal through the analog-to-digital conversion unit, and sends the digital signal to the microprocessor unit;
a microprocessor unit configured to:
Determining a state change event of electric equipment according to a data segment corresponding to the difference between two continuous sampling points, filtering the state change event of the electric equipment to obtain a suspicious event of the electric welding machine to be monitored, carrying out clustering treatment on the suspicious event, and determining a real event of the electric welding machine to be monitored;
And reconstructing the operation state of the electric welding machine to be monitored according to the data segment associated with the real event to obtain the complete operation state of the electric welding machine to be monitored, and realizing the welding machine operation monitoring based on the power grid end.
Further, the current-voltage sensing unit comprises a current transformer and a voltage transformer which are arranged at the monitoring point, and can collect bus voltage and line current signals at a set sampling rate.
Further, the monitoring point is located at least one of the outgoing line of the low-voltage side of the distribution transformer, the outgoing line of each load, the outgoing line of the low-voltage distribution cabinet of the industrial and commercial user and the residential area.
Further, the signal conditioning unit converts the current-voltage analog signal into a standard signal for data acquisition and calculation, including low-pass filtering, range conversion, AD conversion and normalization.
A second aspect of the present invention provides a method for monitoring operation of a welder based on a power grid, comprising the steps of:
Acquiring and preprocessing the current and the voltage of the monitoring point based on the set sampling rate, and determining a state change event of the electric equipment by using a data segment corresponding to the difference between two continuous sampling points;
Filtering state change events of electric equipment to obtain suspicious events of the electric welding machine to be monitored, and carrying out clustering treatment on the suspicious events to determine real events of the electric welding machine to be monitored;
And reconstructing the operation state of the electric welding machine to be monitored according to the data segment associated with the real event to obtain the complete operation state of the electric welding machine to be monitored, and realizing the welding machine operation monitoring based on the power grid end.
Further, the preprocessing includes low-pass filtering, range conversion, AD conversion and normalization.
Further, a state change event of the electric equipment is determined according to a data segment corresponding to the difference between two continuous sampling points, specifically:
Acquiring slope values of all data points, counting all slope points from a certain initial position, stopping counting when the slope values of the data points exceed a threshold value and the difference of slope average values of all the data points after the point and before the point exceeds the threshold value, and obtaining a continuous data segment and a break point;
and processing a new data segment from a point with a non-zero first slope value after the interrupt point until all points of the whole data set are processed, wherein each data segment corresponds to a state change event of electric equipment.
Further, filtering state change events of electric equipment to obtain suspicious events of the electric welding machine to be monitored, and carrying out clustering treatment on the suspicious events to determine real events of the electric welding machine to be monitored; the method comprises the following steps:
Obtaining an event causing the starting of the electric welding machine to be monitored as a suspicious event through a set filtering condition, wherein the filtering condition comprises at least one of an actual active reactive power range, a harmonic content range, the existence of a peak and the continuous working time of equipment;
and obtaining the real event belonging to the electric welding machine to be monitored in the suspicious event based on a clustering algorithm.
Further, reconstructing the operation state of the electric welding machine to be monitored according to the data segment associated with the real event to obtain the complete operation state of the electric welding machine to be monitored; the method comprises the following steps:
and determining the association type according to the occurrence times of the clusters and the set event association standard to obtain independent events, repeated events, accidental events and irrelevant events belonging to the electric welding machine to be monitored, and reconstructing all the events to obtain the complete working state of the electric welding machine to be monitored.
The third aspect of the invention provides a welding machine operation monitoring system based on a power grid end, which comprises at least one group of welding machine operation monitoring devices based on the power grid end, wherein the welding machine operation monitoring devices are arranged at set monitoring points, and each gateway of the Internet of things is utilized to send welding machine operation information to a server, wherein the welding machine operation information comprises position information, current and voltage information and reconstructed working state information of a welding machine;
the server receives the operation information of the electric welding machine obtained by the monitoring device, compares the operation information with fire permission information prestored in the database and pushes a comparison result to the user side;
And the user side receives the pushed comparison result from the server and sends an alarm or prompt to the user.
The one or more of the above technical solutions have the following beneficial effects:
1. According to the load characteristics of the electric welding machine, whether the user load has the operation of the electric welding machine to start fire or not is monitored from the power grid end, and the operation state information of the electric welding machine is obtained without installing sensors on various electric equipment of the user during the monitoring, so that the operation of the electric equipment is not interfered.
2. Detecting state transition events of electric equipment by using slopes between two adjacent sampling points of load electric quantity (power, current and the like) of the monitoring points and a power threshold value, extracting real events related to the electric welding machine to be monitored in the events by filtering and clustering according to load characteristics of the electric welding machine, and monitoring whether the load of the electric welding machine has fire operation or not from a power grid side by using the reconstructed complete working state so as to realize interference-free online monitoring.
3. The monitoring device is simple to use, does not need user maintenance, has strong universality of a monitoring algorithm, and can monitor electric welding machines of different types and different power magnitudes.
4. The monitoring algorithm is completed on each monitoring device, and only the monitoring result and the waveform characteristics before and after the electric welding machine is started are sent to the server, so that the data transmission quantity can be reduced, the reliability of the system is improved, and the integral operation of the system is not affected when a device at one monitoring point fails.
5. The monitoring device can be arranged at several optional positions on the low-voltage side of the power grid distribution transformer, if a fire operation exists, monitoring results and position information are transmitted to the server through the Internet of things and are compared with the fire operation permission information of the electric welding machine stored in the server, if no fire operation application permission exists, warning and position information are pushed, so that the occurrence of fire disasters of the electric welding machine can be effectively prevented, and the investigation work efficiency of fire accidents can be improved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the invention.
FIG. 1 is a schematic diagram of a monitoring device arrangement provided by one or more embodiments of the present invention;
FIG. 2 is a schematic diagram of a hardware configuration of a monitoring device according to one or more embodiments of the present invention;
FIG. 3 is a schematic flow diagram of a monitoring software algorithm provided by one or more embodiments of the present invention;
FIG. 4 is a schematic illustration of a welding bug fire event reconstructed by a software algorithm provided by one or more embodiments of the present invention;
Fig. 5 is a schematic diagram of an electric welding machine fire operation monitoring system based on the internet of things according to one or more embodiments of the present invention.
In the figure: 1 medium voltage distribution bus, 2 low voltage distribution transformer, 3 monitoring device, 4 load outlet cabinet, 5 user switch board.
Detailed Description
The invention will be further described with reference to the drawings and examples.
It should be noted that the following detailed description is exemplary and is intended to provide further explanation of the invention. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.
As described in the background art, the existing electric welding machine monitoring technology collects state information of an electric welding machine body at a production construction site, and is mainly used for welding quality control and site safety management, for example:
CN110826439A monitors electric welding construction operation of enterprises in the jurisdiction by analyzing video monitoring pictures in the factory;
CN110640266A, a monitoring circuit is arranged on the electric welding machine body, voltage and current information of the electric welding machine body is collected and transmitted through RS485-GPRS, and the purpose of fault analysis and operation optimization of the electric welding machine is achieved;
CN106325247A is used for collecting the input current and voltage of the electric welding machine body, obtaining the dynamic information of the electric welding machine through comprehensive calculation, and transmitting the dynamic information to the background through a temporary power distribution box in a power carrier mode, so that a construction manager can conveniently grasp the dynamic information of the electric welding machine on a construction site in time;
CN114282689A, utilizing a current sensor to collect current data of an electric welding machine in the welding process on line, and designing a characteristic algorithm based on an arcing signal mechanism based on the research of actual industrial welding arcing data, wherein the characteristic algorithm is used for on-line detection of an arcing event;
CN115685908A, through on-line detection of environmental parameters and welding process parameters, and timely give an alarm and prompt, reduces the safety risk of construction operators.
The monitoring mode is realized by collecting information of the electric welding machine itself or the environment, and is generally used for welding quality control and field safety management, and some potential risks existing in the operation period of the electric welding machine cannot be mastered, for example, when the electric welding machine is used for fire operation, a fire department cannot obtain operation information of the electric welding machine, and whether the fire operation of the electric welding machine is permitted or not cannot be mastered, so that certain fire safety hidden danger is generated.
For the electric network, various types of electric welding machines can be understood as a power down-converter capable of outputting large current, therefore, the following embodiments provide a welding machine operation monitoring device, method and system based on the electric network end, through several setting positions installed on the low-voltage side of the distribution transformer of the electric network, the load borne by the distribution transformer can be monitored on line without interference whether the electric welding machine operates on fire, if so, the monitoring result and the position information are transmitted to a fire server or a cloud platform through the internet of things, and compared with the electric welding machine operates on fire permission information stored in the server, if no operation is applied for permission, an alarm and the position information are sent to a user (such as a mobile terminal APP). Not only can effectively prevent the occurrence of fire disasters of the electric welding machine, but also can improve the investigation work efficiency of fire accidents.
Embodiment one:
welding machine operation monitoring devices based on electric wire netting end includes:
the current and voltage sensing unit is used for acquiring current and voltage data of a set monitoring point and sending the current and voltage data to the signal conditioning unit;
the signal conditioning unit is used for preprocessing the received data and sending the data to the analog-to-digital conversion unit;
the analog-to-digital conversion unit converts the preprocessed analog signals into digital signals and sends the digital signals to the microprocessor unit;
a microprocessor unit configured to:
determining a state change event of electric equipment according to a data segment corresponding to the difference between two continuous sampling points, filtering the state change event of the electric equipment to obtain a suspicious event of the electric welding machine to be monitored, carrying out clustering treatment on the suspicious event, and determining a real event of the electric welding machine to be monitored;
And reconstructing the operation state of the electric welding machine to be monitored according to the data segment associated with the real event to obtain the complete operation state of the electric welding machine to be monitored, and realizing the welding machine operation monitoring based on the power grid end.
As shown in fig. 1, the monitoring device 3 may be arranged in a low-voltage side load outlet cabinet 4 connected with a low-voltage distribution transformer 2 of a medium-voltage distribution busbar 1 of a power distribution network 10.5kV/0.4kV, or in a user power distribution cabinet 5; the monitoring device inputs the bus voltage and the line current; the current sensing unit is arranged on the load bus or the branch line; the closer the monitoring device is to the load end, the more accurate the positioning of the welding machine, which has the disadvantage of increasing the number of the monitoring devices and increasing the cost. In general, the device can be installed on a low-voltage side load outlet cabinet of a distribution transformer.
For example, loads include commercial, residential and industrial loads, with different consumer status events in different load types, commercial loads including, but not limited to, start and stop of electric welders, showcases, central air conditioning, charging piles, lighting, and elevators; various household appliances in resident load are started and stopped; start-stop of various industrial equipment in industrial load, etc.
As shown in fig. 2, the monitoring device comprises a current and voltage sensing unit, a signal conditioning unit, a data acquisition unit, a microprocessor unit, a communication unit, an input display unit, a power management unit, a storage unit, a GPS/Beidou positioning unit and an internet of things gateway. Wherein the microprocessor unit integrates a signal conditioning unit.
The current and voltage sensing unit senses current and voltage data of a monitoring point on the low-voltage side of the distribution transformer in real time and sends the current and voltage data to the signal conditioning unit; the signal conditioning unit is used for preprocessing the received information and then sending the preprocessed information to the analog-to-digital conversion unit; the analog-to-digital conversion unit converts the conditioned analog signals into digital signals and sends the digital signals to the microprocessor unit; the microprocessor unit judges whether the electric welding machine is started and operated at the downstream of the monitoring point according to the operation characteristics of the electric welding machine, the steady state characteristics, transient steady state characteristics, harmonic characteristics and the like of the start-stop work; if an electric welding machine works, transmitting a judging result and position information to a server through an Internet of things gateway by utilizing a communication unit; inquiring the ignition work permission information of the electric welding machine at the server, and pushing alarm and position information to the user if no ignition work application permission exists. The position information is acquired through a GPS/Beidou positioning unit.
In this embodiment, the current-voltage sensing unit refers to a monitoring point Current Transformer (CT) and a voltage transformer (PT), and can collect bus voltage and line current signals at a certain sampling rate, and can select outgoing lines installed on the low-voltage side of the distribution transformer, outgoing lines of various loads, outgoing lines of industrial and commercial users and low-voltage distribution cabinets in residential areas according to actual needs.
In this embodiment, the signal conditioning unit converts the current-voltage analog signal into a standard signal for data acquisition and calculation, and mainly includes low-pass filtering, range conversion, AD conversion and normalization; wherein the filtering is performed with a low-pass filter having a cut-off frequency of 500Hz, which is specified by an anti-aliasing filter of the signal conditioning unit; to prevent noise in the signal from being detected as a device start-stop event, the instantaneous power signal is median filtered.
In this embodiment, the analog-to-digital conversion unit converts the conditioned analog signal into a digital signal and then uses software to process the digital signal; according to the load characteristics of the electric welding machine, the sampling frequency is usually not higher than 10 times of harmonic waves, and the sampling frequency can be set to be 0.2-2 KHz.
In this embodiment, the microprocessor unit and the storage unit run a computer program to execute the functions of the electric welding machine fire operation monitoring algorithm, input/output display communication and the like.
Embodiment two:
The welding machine operation monitoring method based on the power grid end comprises the following steps:
acquiring and preprocessing the current and the voltage of the monitoring point based on the set sampling rate to obtain the slope of the sampling data point, and determining a state change event of the electric equipment according to the data segment corresponding to the difference between two continuous sampling points;
Filtering state change events of electric equipment to obtain suspicious events of the electric welding machine to be monitored, and carrying out clustering treatment on the suspicious events to determine real events of the electric welding machine to be monitored;
And reconstructing the operation state of the electric welding machine to be monitored according to the data segment associated with the real event to obtain the complete operation state of the electric welding machine to be monitored, and realizing the welding machine operation monitoring based on the power grid end.
As shown in fig. 3, the microprocessor unit performs a welding machine fire operation detection algorithm, pre-processes collected data, detects a state change event of electric equipment, filters the state change event of the electric equipment to obtain a suspicious event of a specific welding machine, clusters the suspicious event to determine a real event, and reconstructs the fire operation state of the welding machine to obtain a complete operation state of the welding machine so as to realize welding machine operation monitoring based on a power grid end.
And detecting the state transition event of the electric equipment, namely detecting the start (ON) and stop (OFF) of the equipment and the running state change. The present embodiment does not directly find a state transition, but finds all consecutive data segments, and then treats the portion between two adjacent data segments as a state transition event.
For example, the slope may be used as an effective indicator for determining the continuity of a data segment, i.e. a point in a data segment with good continuity should have a small slope, or a continuous point where all slope values are close to zero may be considered as one continuous data segment.
（1）
The monitoring point is used for aggregating load electric quantity such as power, current and the like; /(I)Is the difference between two consecutive sample points,；/>Is the time difference between two sampling points, i.e. the acquisition interval, if the sampling rate is 1.5K, then/>About 0.00066 seconds. Because/>Is a fixed value, the slope depends on/>. The event detection algorithm comprises the following steps:
step 1: calculating slope values of all data points; in this embodiment, the slope value is obtained by calculating the difference between two sampling points and dividing by the sampling point time interval. If the sampling interval is 1 second, the slope is the difference between the two sampling points.
Step 2: counting all points smaller than the set slope from a certain initial position, stopping counting when the slope value of a data point exceeds a threshold value and the difference of the average values of stable points after the point and before the point exceeds the threshold value, and obtaining a continuous data segment and a break point; since the ON and OFF events of the welding bug are close to a step change (90 degrees), the present embodiment sets the tangent of 60 degrees as the threshold.
And 3, processing a new data segment from the point, which is close to zero, of the first slope value after the break point, wherein the data segment is a data set formed by all continuous points, which are close to zero, of the slope value, and repeating the step2 until all points of the whole data set are processed.
The suspicious event of the specific equipment is obtained through the filtering of the state change event of the electric equipment, namely, a group of ON events possibly but not necessarily caused by the equipment is obtained through the filtering of the event. In other words, the actual events related to the specific equipment welder are kept as far as possible. The conditions for achieving the filtration are as follows: the actual active and reactive power range, the harmonic content range, the presence or absence of spikes, the continuous operation time of equipment and the like. In order to ensure that events of various types of welding bug may be contained, the filtering conditions should not be set too stringent.
The filtration conditions in this example are as follows:
1) The type, specification and power of the electric welding machine are different according to different application scenes and needs. The alternating current welder is usually between 1 and 10kW, and the power factor is about 0.5; the variable frequency type electric welding machine is generally between 5 and 20 kW; the direct current electric welding is generally above 10kW, and the power factor is above 0.9;
2) Because the welding current of the electric welding machine is controlled by adopting a silicon controlled rectifier or an inverter, rich harmonic components can be generated, and the frequency of the harmonic components is generally not more than 9 times odd harmonic. The AC welder generally comprises 2, 3, 4 and 5 harmonics, and the total harmonic distortion THD is more than 50%; the direct current electric welding machine mainly comprises 3-19 odd harmonics, and total harmonic distortion THD is more than 200%;
3) The electric welder is equivalent to a high-power buck converter, and the secondary side is equivalent to short circuit at the moment when the welding rod contacts (ON) welding pieces, so that great current jump occurs, the alternating current electric welder is more than 30A, and the direct current electric welder is more than 40A; when the electrode is disengaged (OFF) from the weldment, the secondary side corresponds to an open circuit and the current jump becomes zero. To improve processing efficiency, only ON events are validated, as transient features are only accompanied by ON events, which are subsequently considered by inspection as potential suspicious events;
4) The working principle and the operation mode of the electric welding machine determine intermittent conduction in a short time under the working state, and the electric welding machine has unique intermittence. The electric welding machine generally has two working modes of spot welding and long welding, wherein the spot welding interval is about 1 second, the long welding interval is about 3 seconds, and the continuous working time of 30 seconds can be selected as a search window.
Clustering of the state change events of the electric equipment, namely, further determining which suspicious events are real events belonging to a specific electric welding machine by using a clustering method. The clustering is based on the fact that in a suspicious event group of the electric welding machine, the number of events belonging to the electric welding machine should be far more than events belonging to other electric equipment. If the number of event groups and the number of events each group has are known, then the actual event can be determined to be the most membership event in the event group.
The cluster analysis algorithm determines which events are approximately the same and may be combined together as a cluster. After event filtering, because the clustering space is greatly reduced, a lot of uncertainty and noise can be eliminated, and the clustering can be completed faster and more accurately.
The clustering method comprises K-means clustering, fuzzy clustering, mean shift clustering, weight-based clustering and the like. Taking weight-based clustering as an example, the steps are as follows:
step 1: initializing random events into single element clusters;
Step 2: the other events are compared one by one with the existing cluster mean. If the event is sufficiently similar to the cluster mean, the event is merged into the same cluster and the cluster mean is updated. If the event is not similar to any existing cluster mean, marking the event as a new single element cluster;
Step 3: the existing cluster mean is treated as a single event and steps 1 and 2 are redone. If the two cluster means are similar enough, the two corresponding clusters are combined into a new cluster;
Step 4: the iteration is continued until there is no cluster update.
To quantify the similarity between an event and a cluster average or two cluster averages, the following formula may be used:
（2）
（3）
（4）
（5）
In the above-mentioned method, the step of, Weights assigned to the electrical quantity P, Q and THD according to the device class information; where subscript c represents the cluster mean and e represents a particular event; /(I)For the active reactive power of a specific event,/>Active reactive power is clustered average; s p、Sq and S h are child similarity indices, S is an overall similarity index. After the overall similarity index S is calculated, it may be compared to some defined threshold (e.g., 0.8) to determine if the event is sufficiently similar to the cluster mean.
And reconstructing the fire operation state of the electric welding machine, namely reconstructing the complete operation state of the electric welding machine, wherein the complete operation state comprises a start-stop event and an intermediate event. This step calculates the number and frequency of occurrence of the event to determine whether the event is associated with a particular device and to determine whether the type of association of the event is a welding bug with a repetitive nature.
The specific steps of searching for device association events and determining association types are as follows:
step 1: m data segments to be associated are determined, each data segment having the same length. A data segment is defined as a segment of data whose beginning has a true ON event and is of moderate length. A data segment that is too short may not include all relevant events of the welder and too long may include more irrelevant disturbance events. The embodiment selects 30 seconds as the operation duration of the electric welding machine;
Step2: when event association starts, the clustering method is applied to all events included in the M data segments again, so that each event can be marked by the cluster number to which each event belongs;
Step 3: counting the occurrence times of each cluster, and then determining the association type AT according to the event association standard of the formula (6);
（6）
For individual events to occur only once in a run period, the number of events N should be equal to the number of data segments M; for repeated events, once the device is working, this event must occur and occur multiple times in one run or operating cycle, so the number of events N should be greater than M; for sporadic events, which have a weak association with the device, once the device is operating properly, this event may not occur, which should occur more frequently than the threshold specified by b. The factor b may distinguish whether the event is related to the target device. The theoretical criteria are further corrected using confidence c and other conditions, with the values of b and c typically set to 0.3 and 0.8, respectively, taking into account false clusters or event losses that may occur due to improper data segmentation.
To improve the association accuracy, more data segments need to be used. The more data segments, the less likely an uncorrelated event is misinterpreted as a correlated event due to improper selection of confidence factors b and c. In addition, the more data segments, the influence of missing events caused by clustering errors or improper data segmentation can be reduced to the minimum. The reconstructed welding machine fire operation event is shown in fig. 4.
Embodiment III:
as shown in fig. 5, the welding machine operation monitoring system based on the power grid end includes:
The welding machine operation monitoring device based on the power grid end is arranged at each monitoring point, and the position information, the current and voltage information and the reconstructed operation state of the welding machine are sent to the server through the gateway of the respective Internet of things;
The server, in this embodiment, a cloud server or an entity server, has: data storage, inquiry and statistics functions, and license management functions of electric welding machines, welders and work and fire operation, and web publishing and information pushing functions; the information pushing function is utilized to compare and analyze the information of the electric welding machine fire operation with the fire permission information in the database to push the result to the user side;
the user terminal in this embodiment is a mobile terminal APP, and is configured to receive the pushed alarm and prompt information from the server.
The above description is only of the preferred embodiments of the present invention and is not intended to limit the present invention, but various modifications and variations can be made to the present invention by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. Welding machine operation monitoring devices based on electric wire netting end, its characterized in that includes following steps:
The current and voltage sensing unit acquires current and voltage data of a set monitoring point, performs preprocessing on the received data through the signal conditioning unit, converts the preprocessed analog signal into a digital signal through the analog-to-digital conversion unit, and sends the digital signal to the microprocessor unit;
a microprocessor unit configured to:
determining a state change event of electric equipment according to a data segment corresponding to the difference between two continuous sampling points, filtering the state change event of the electric equipment to obtain a suspicious event of the electric welding machine to be monitored, carrying out clustering treatment on the suspicious event, and determining a real event of the electric welding machine to be monitored;
And reconstructing the operation state of the electric welding machine to be monitored according to the data segment associated with the real event to obtain the complete operation state of the electric welding machine to be monitored, and realizing the welding machine operation monitoring based on the power grid end.
2. The grid-side based welder operation monitoring device of claim 1, wherein the current-voltage sensing unit includes a monitoring point current transformer and a voltage transformer arranged to collect bus voltage and line current signals at a set sampling rate.
3. The grid-side based welder operation monitoring device of claim 1, wherein the monitoring point is located at least one of a distribution transformer low voltage side outlet, a load outlet, a business user, and a residential low voltage power distribution cabinet outlet.
4. The utility-side welder operation monitoring device of claim 1, wherein the signal conditioning unit converts the current-voltage analog signal to a standard signal for data acquisition, performing calculations, including low pass filtering, span conversion, AD conversion, and normalization.
5. The welding machine operation monitoring method based on the power grid end is characterized by comprising the following steps of:
Acquiring and preprocessing the current and the voltage of the monitoring point based on the set sampling rate, and determining a state change event of the electric equipment by using a data segment corresponding to the difference between two continuous sampling points;
Filtering state change events of electric equipment to obtain suspicious events of the electric welding machine to be monitored, and carrying out clustering treatment on the suspicious events to determine real events of the electric welding machine to be monitored;
And reconstructing the operation state of the electric welding machine to be monitored according to the data segment associated with the real event to obtain the complete operation state of the electric welding machine to be monitored, and realizing the welding machine operation monitoring based on the power grid end.
6. The grid-side based welder operation monitoring method of claim 5, wherein the preprocessing includes low pass filtering, span conversion, AD conversion, and normalization.
7. The welding machine operation monitoring method based on the power grid end as set forth in claim 5, wherein the determining the electric equipment state change event according to the data segment corresponding to the difference between two consecutive sampling points is specifically:
Acquiring slope values of all data points, counting all slope points from a certain initial position, stopping counting when the slope values of the data points exceed a threshold value and the difference of slope average values of all the data points after the point and before the point exceeds the threshold value, and obtaining a continuous data segment and a break point;
and processing a new data segment from a point with a non-zero first slope value after the interrupt point until all points of the whole data set are processed, wherein each data segment corresponds to a state change event of electric equipment.
8. The welding machine operation monitoring method based on the power grid end as set forth in claim 5, wherein the state change event of the electric equipment is filtered to obtain suspicious events of the electric welding machine to be monitored, and the suspicious events are clustered to determine real events of the electric welding machine to be monitored; the method comprises the following steps:
Obtaining an event causing the starting of the electric welding machine to be monitored as a suspicious event through a set filtering condition, wherein the filtering condition comprises at least one of an actual active reactive power range, a harmonic content range, the existence of a peak and the continuous working time of equipment;
and obtaining the real event belonging to the electric welding machine to be monitored in the suspicious event based on a clustering algorithm.
9. The welding machine operation monitoring method based on the power grid end according to claim 5, wherein the operation state of the welding machine to be monitored is reconstructed according to the data segment associated with the real event, so as to obtain the complete operation state of the welding machine to be monitored; the method comprises the following steps:
and determining the association type according to the occurrence times of the clusters and the set event association standard to obtain independent events, repeated events, accidental events and irrelevant events belonging to the electric welding machine to be monitored, and reconstructing all the events to obtain the complete working state of the electric welding machine to be monitored.
10. A welding machine operation monitoring system based on a power grid end, which is characterized by comprising at least one group of welding machine operation monitoring devices based on the power grid end, wherein the welding machine operation monitoring devices are arranged at set monitoring points, and each gateway of the internet of things is utilized to send welding machine operation information to a server, wherein the welding machine operation information comprises position information, current and voltage information and reconstructed working state information of a welding machine;
the server receives the operation information of the electric welding machine obtained by the monitoring device, compares the operation information with fire permission information prestored in the database and pushes a comparison result to the user side;
And the user side receives the pushed comparison result from the server and sends an alarm or prompt to the user.
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