CN114239790A - Water heater tank yield statistical method and device with model identification function - Google Patents
Water heater tank yield statistical method and device with model identification function Download PDFInfo
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Abstract
The invention provides a statistical method and a device for the yield of a water heater tank body with a model identification function, wherein the method comprises the steps of using current data and voltage data obtained by decoding as welding process data of a water heater liner; dividing the process data into a plurality of process data sections, shaping the current and voltage time sequence data in each process data section, and determining the welding machine state corresponding to each process data section; judging each process data segment, and determining corresponding total welding time; determining whether to count according to the total welding time; and acquiring all tank identifications recorded in the database and the total welding time corresponding to the tank identifications, and classifying the water heater tanks. The method provides an unmanned counting scheme with real-time statistics for field arc welding quality detection, overcomes the defect of low accuracy in the prior art, does not need manual recording of workers, improves the counting accuracy and reduces the workload of the workers.
Description
Technical Field
The invention relates to the field of monitoring, in particular to a water heater tank yield statistical method and device with a model identification function.
Background
When producing related parts of an electric water heater, for example, when producing an inner container of the electric water heater, output statistics and model identification need to be performed on the inner container of the electric water heater, the existing statistical mode is that counting is performed through a PLC (programmable logic controller) arranged in a special welding machine, and the PLC sends control commands, such as control commands of tool closing, welding machine power-on, welding machine power-off, tool closing and the like, to a welding machine and a tool clamp in the welding process. After a complete working cycle, the PLC is regarded as welding a tank body, daily output data are accumulated, the accumulated result is displayed on an external screen of a special machine, and staff copy and record the accumulated result every day.
However, the above-described method of counting by PLC has the following problems: the cans that have undergone a complete duty cycle are counted to account for production, but arc breaks, manual interruption of the duty cycle, etc. occur during the actual welding process. If the arc breaking phenomenon occurs in the welding process, the welding process still continues until the whole welding process is completed, and thus the number of the tank bodies with arc breaking in the welding process is counted. And after the tank body with the arc breakage in the welding process is checked and found by staff, the tank body with the arc breakage in the welding process can be installed into the tool again for welding again, and PLC repeated counting is caused at the moment.
For another example, if a worker manually interrupts the welding cycle after welding is complete, for example, by manually removing the can for inspection and then manually returning the can to the production line, the PLC will not count, but at this point a omission occurs because the welding has actually been completed.
In addition, the water heater tanks of different models have different sizes, and the total production of the line bodies can be obtained only through duty cycle counting, so that the production of the water heater tanks of all sizes cannot be accurately counted.
Disclosure of Invention
In order to solve the technical problems, the invention provides a method and a device for counting the yield of a water heater tank with a model identification function, which are used for solving the technical problems that the model of the water heater cannot be identified and the yield of the water heater tank cannot be accurately counted in the prior art.
According to a first aspect of the invention, a statistical method for the production of a water heater tank with a model identification function is provided, wherein the statistical method comprises the following steps:
step S101: configuring a Hall current sensor and a voltage sensor for a welding machine, wherein the circular ring of the Hall current sensor is sleeved on a cable at the current output end of the welding machine, and the Hall current sensor detects the current of a welding loop of the welding machine; the voltage inductor is connected with a power supply of the welding machine in parallel and used for detecting the voltage of a main loop of the welding machine; the Hall current sensor and the voltage sensor simulate the detected data into weak current analog signals, and the Internet of things gateway decodes the weak current analog signals to obtain current and voltage data; using the decoded current data, voltage data and gas flow data as water heater liner welding process data, wherein the process data are time sequence data;
step S102: dividing the process data of the water heater inner container into a plurality of process data sections, shaping the current and voltage time sequence data in each process data section, and determining the welding machine state corresponding to each process data section based on the processed current data and voltage data;
step S103: setting a variable F, S, T, wherein F is used for marking whether arcing is performed, S is used for marking an arcing time point, T is used for marking the total welding time, the initial value of the variable F is false, the initial value of S is-1, and the initial value of T is-1;
step S104: judging whether the states of the welding machines corresponding to all the process data sections are counted up, if so, entering the step S106; if not, acquiring a welder state corresponding to the process data section which is not subjected to statistics according to the time sequence, and entering the step S105;
step S105: if the welder state corresponding to the non-counted process data segment is an arc starting welding stage, setting a variable F to be true, and setting a variable S to be a time point corresponding to an arc starting position in the process data segment; entering step S104;
if the welding machine state corresponding to the non-counted process data segment is a standby state or a welding state, the variable value is not changed; entering step S104;
if the state of the welding machine corresponding to the non-counted process data segment is an arc-ending time segment, if the value of the variable F is true, acquiring a time point corresponding to an arc-ending position in the process data segment, taking the difference value between the time point corresponding to the arc-ending position and the variable S as the total welding time length, and setting the variable T as the total welding time length;
if the total welding time is less than 20 seconds, the total number of the tank bodies is not counted, and the step S103 is carried out;
if the total welding time is longer than or equal to 20 seconds, adding 1 to the total number of the tank bodies in the database, recording the tank body identification of the newly counted tank body and the total welding time corresponding to the tank body identification, and entering the step S103;
step S106: acquiring all tank identifications recorded in a database and total welding time corresponding to the tank identifications, and identifying the tanks with the total welding time difference within 2 seconds as water heater tanks of the same model; and counting and displaying the number of the water heater tank bodies of each model and the identification of the water heater tank bodies of each model.
According to a second aspect of the present invention, there is provided a water heater tank production statistic device with model identification function, the device comprising:
a data acquisition module: configuring a Hall current sensor and a voltage sensor for the welding machine, wherein the circular ring of the Hall current sensor is sleeved on a cable at the current output end of the welding machine, and the Hall current sensor detects the current of a welding loop of the welding machine; the voltage inductor is connected with a power supply of the welding machine in parallel and used for detecting the voltage of a main loop of the welding machine; the Hall current sensor and the voltage sensor simulate the detected data into weak current analog signals, and the Internet of things gateway decodes the weak current analog signals to obtain current and voltage data; using the decoded current data, voltage data and gas flow data as water heater liner welding process data, wherein the process data are time sequence data;
the welding machine state determination module: dividing the process data of the water heater inner container into a plurality of process data sections, shaping the current and voltage time sequence data in each process data section, and determining the welding machine state corresponding to each process data section based on the processed current data and voltage data;
an initialization module: setting a variable F, S, T, wherein F is used for marking whether arcing is performed, S is used for marking an arcing time point, T is used for marking the total welding time, the initial value of the variable F is false, the initial value of S is-1, and the initial value of T is-1;
a judging module: the method comprises the steps that whether the states of the welding machines corresponding to all process data sections are counted is judged, and if yes, a counting module is triggered; if not, acquiring a welder state corresponding to the process data section which is not subjected to statistics according to the time sequence, and triggering a state statistics module;
a state statistics module: setting a variable F to be true if the state of the welding machine corresponding to the non-counted process data segment is an arc starting welding stage, and setting a variable S to be a time point corresponding to an arc starting position in the process data segment; a triggering judgment module;
if the welding machine state corresponding to the non-counted process data segment is a standby state or a welding state, the variable value is not changed; a triggering judgment module;
if the state of the welding machine corresponding to the non-counted process data segment is an arc-ending time segment, if the value of the variable F is true, acquiring a time point corresponding to an arc-ending position in the process data segment, taking the difference value between the time point corresponding to the arc-ending position and the variable S as the total welding time length, and setting the variable T as the total welding time length;
if the total welding time is less than 20 seconds, the total number of the tank bodies is not counted, and an initialization module is triggered;
if the total welding time is more than or equal to 20 seconds, adding 1 to the total number of the tank bodies in the database, recording the tank body identification of the newly counted tank body and the total welding time corresponding to the tank body identification, and triggering an initialization module;
a statistic module: the method comprises the steps that all tank body identifications recorded in a database and total welding time corresponding to the tank body identifications are obtained, and the tank bodies with the total welding time difference within 2 seconds are identified as water heater tank bodies of the same type; and counting and displaying the number of the water heater tank bodies of each model and the identification of the water heater tank bodies of each model.
According to a third aspect of the invention, a water heater tank production statistical system with model identification function is provided, which comprises:
a processor for executing a plurality of instructions;
a memory to store a plurality of instructions;
wherein the instructions are used for being stored by the memory and loaded and executed by the processor to perform the statistical method for the production of the water heater tank with the model identification function.
According to a fourth aspect of the present invention, there is provided a computer readable storage medium having a plurality of instructions stored therein; the instructions are used for loading and executing the statistical method for the production of the water heater tank with the model identification function by the processor.
According to the scheme, the method designs the water heater tank yield statistical method with the model identification function by collecting the data of the arc signals in the welding process and combining with an industrial intelligent algorithm, and can accurately count the yield of the water heater tanks of various models so as to accurately account the production capacity of a production line and realize the fine management of factory materials. The method provides an unmanned counting scheme with real-time statistics for field arc welding quality detection, overcomes the defect of low accuracy in the prior art, does not need manual recording of workers, improves the counting accuracy and reduces the workload of the workers.
The foregoing description is only an overview of the technical solutions of the present invention, and in order to make the technical solutions of the present invention more clearly understood and to implement them in accordance with the contents of the description, the following detailed description is given with reference to the preferred embodiments of the present invention and the accompanying drawings.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and, together with the description, serve to explain the principles of the invention. In the drawings:
FIG. 1 is a schematic flow chart of a statistical method for production of a water heater tank with model identification function according to an embodiment of the present invention;
fig. 2 is a schematic diagram of a data acquisition device according to an embodiment of the present invention.
Reference numerals:
1: industrial routing; 2: a voltage inductor; 3: a current sensor; 4, edge computing gateway; 5: welding gun
Detailed Description
First, a flow of a statistical method for the production of a water heater tank with a model identification function according to an embodiment of the present invention is described with reference to fig. 1. As shown in fig. 1-2, the method comprises the steps of:
step S101: configuring a Hall current sensor and a voltage sensor for a welding machine, wherein the circular ring of the Hall current sensor is sleeved on a cable at the current output end of the welding machine, and the Hall current sensor detects the current of a welding loop of the welding machine; the voltage inductor is connected with a power supply of the welding machine in parallel and used for detecting the voltage of a main loop of the welding machine; the Hall current sensor and the voltage sensor simulate the detected data into weak current simulation signals, and the Internet of things gateway decodes the weak current signals to obtain current and voltage data; using the decoded current data, voltage data and gas flow data as water heater liner welding process data, wherein the process data are time sequence data;
step S102: dividing the process data of the water heater inner container into a plurality of process data sections, shaping the current and voltage time sequence data in each process data section, and determining the welding machine state corresponding to each process data section based on the processed current data and voltage data;
step S103: setting a variable F, S, T, wherein F is used for marking whether arcing is performed, S is used for marking an arcing time point, T is used for marking the total welding time, the initial value of the variable F is false, the initial value of S is-1, and the initial value of T is-1;
step S104: judging whether the states of the welding machines corresponding to all the process data sections are counted up, if so, entering the step S106; if not, acquiring a welder state corresponding to the process data section which is not subjected to statistics according to the time sequence, and entering the step S105;
step S105: if the welder state corresponding to the non-counted process data segment is an arc starting welding stage, setting a variable F to be true, and setting a variable S to be a time point corresponding to an arc starting position in the process data segment; entering step S104;
if the welding machine state corresponding to the non-counted process data segment is a standby state or a welding state, the variable value is not changed; entering step S104;
if the state of the welding machine corresponding to the non-counted process data segment is an arc-ending time segment, if the value of the variable F is true, acquiring a time point corresponding to an arc-ending position in the process data segment, taking the difference value between the time point corresponding to the arc-ending position and the variable S as the total welding time length, and setting the variable T as the total welding time length;
if the total welding time is less than 20 seconds, the total number of the tank bodies is not counted, and the step S103 is carried out;
if the total welding time is longer than or equal to 20 seconds, adding 1 to the total number of the tank bodies in the database, recording the tank body identification of the newly counted tank body and the total welding time corresponding to the tank body identification, and entering the step S103;
step S106: acquiring all tank identifications recorded in a database and total welding time corresponding to the tank identifications, and identifying the tanks with the total welding time difference within 2 seconds as water heater tanks of the same model; and counting and displaying the number of the water heater tank bodies of each model and the identification of the water heater tank bodies of each model.
In the step S101, as shown in fig. 2, a hall current sensor and a voltage sensor are configured for the welding machine, an input ring of the hall current sensor is sleeved on a cable ring of a current output end of the welding machine, and the hall current sensor detects a current of a loop of the welding machine; the voltage inductor is connected with a power supply of the welding machine in parallel and used for detecting the voltage of a main loop of the welding machine. In this embodiment, the hall current sensor is a current sensor for detecting a current of a loop of the welding machine. The voltage inductor is installed in the way of being connected in parallel to the positive pole and the negative pole of the power supply, and the voltage of the main loop is measured by utilizing the principle that the voltage of the parallel circuit is equal to the voltage of the main loop. In this embodiment, the main parameters of the current sensor are: the diameter of a welding gun power cable is 20mm, the input current is 0-500A, and the output signal is 0-5V. The main parameters of the voltage sensor are: input voltage 0-100V, output signal: 0-5V.
The sensor simulates the measured data into a 0-5V weak current signal and transmits the weak current signal to the Internet of things gateway, and the Internet of things gateway decodes the weak current signal according to the received simulated weak current signal and outputs finally measured current and voltage data.
In the embodiment, the welding machine is provided with the Hall sensor and the voltage sensor, detected data are simulated into weak current signals, the weak current signals are decoded by the gateway of the internet of things, and the current and voltage data obtained by decoding can be used for collecting arc signals in the welding process.
The step S102: dividing the process data of the water heater inner container welding into a plurality of process data sections, shaping the current and voltage time sequence data in each process data section, and determining the welding machine state corresponding to each process data section based on the processed current data and voltage data, comprising the following steps:
step S1021: dividing the process data of the welding of the inner container of the water heater into a plurality of process data sections by taking 2 seconds as a unit;
step S1022: shaping the current and voltage time sequence data in each process data segment; the shaping treatment is as follows:
carrying out peak clipping and valley filling on original current and voltage time sequence data in a process data section by utilizing mean filtering, and specifically, selecting a plurality of sampling points uniformly for the process data section, taking three adjacent sampling points as a group, and dividing the sampling points of the process data section into a plurality of groups; and for each group, calculating the average value of the three sampling points in the group, and replacing the original current and voltage time sequence data in the corresponding process data section of the group by the average value of the three sampling points in the group.
And after shaping, the current and voltage time sequence data in each process data segment are shaped into square waves.
Step S1023: for each shaped process data segment, the following operations are executed:
acquiring current and voltage time sequence data after the shaping processing of the process data segment, adding the processed current and voltage time sequence data corresponding to the same time point, taking the added result as an electric signal, and obtaining an electric signal sequence according to a time sequence;
for each electric signal in the electric signal sequence, judging whether the electric signal is greater than a welding threshold value, and if the electric signal is greater than or equal to the welding threshold value, updating the electric signal to be 1; if the current value is less than the welding threshold value, updating the electric signal to be 0;
after all the electric signals of the electric signal sequence are processed, splicing the updated electric signals according to the time sequence to generate updated time sequence data of the process data segment, wherein the updated time sequence data is time sequence data consisting of 0 and 1; the updated time sequence data of the process data segment are subjected to derivation, namely the position derivation result which is increased from 0 to 1 is 1, and the position derivation result which is decreased from 1 to 0 is-1; summing the results after the derivation to obtain a final summation result of the process data section;
if the final summation result of the process data segment is 0, determining that the state of the welding machine corresponding to the process data segment is a standby state or a welding state; if the final summation result of the process data segment is greater than or equal to 1, determining that the state of the welding machine corresponding to the process data segment is an arc starting welding stage; and if the final summation result of the process data segment is less than or equal to-1, determining that the state of the welding machine corresponding to the process data segment is an arc-closing time segment.
The principle of performing derivation and then summing the derivation results is as follows: before derivation, the electric signal corresponding to the addition result is a square wave, and because the electric signal corresponding to the addition of the current and voltage time sequence data is 1 when welding, and the electric signal corresponding to the addition of the current and voltage time sequence data is 0 when not welding; the position derivative of which the value is increased from 0 to 1 is 1, the position derivative of which the value is decreased from 1 to 0 is-1, the result of the position derivative of which the value is increased from 1 to 1 is 0, the result of the partial derivative of which the value is constant to 0 or constant to 1 is 0, the derivative results are summed, if the summed result is greater than or equal to 1, the electric signal data has a point (namely an arc starting point) of which the value is increased from 0 to 1, if the summed result is less than or equal to-1, the electric signal data has a point (namely an arc receiving point) of which the value is decreased from 1 to 0, and the result can be used for identifying whether the process data segment is arc receiving or arc starting.
In this embodiment, the time duration corresponding to each process data segment is 2 seconds, and within the time of 2 seconds, there are multiple time points, so that the current data and the voltage data processed by the process data segment are obtained, and the processed current data and the processed voltage data corresponding to the same time point can be added.
In this embodiment, the welding threshold is 10, that is, when the sum of the current and the voltage is greater than 10, it is considered to be welding, otherwise, it is considered to be in standby. The current and voltage are extremely small when the welding is not carried out generally, the current can reach 200A when the welding is carried out normally, the voltage can reach about 30V, and the value of the welding threshold is determined to be 10 through data statistics.
In this embodiment, the current and the voltage are indexes reflecting whether the welder works, and theoretically, whether the welder works can be judged by using any data, but in the actual welding process, the situation that the current is 0, the voltage is not 0, or the voltage is 0, and the current is not 0 exists. In order to avoid the situation of misjudgment, the current and voltage time sequence data are shaped, and the processed current and voltage time sequence data corresponding to the same time point are added for judgment.
In this embodiment, in step S105, if the total welding duration is greater than 20 seconds, it is determined that a complete water heater tank is welded, the types of the water heater tanks are classified according to the total welding duration, and the water heater tanks with the total welding duration within 2 seconds are identified as the water heater tanks of the same model. The purpose of judging the total welding time is to avoid short-time trial welding to be identified as a complete water heater tank.
In this embodiment, in step S106, the database may store data in a certain time period, perform aggregation statistics on the data in units of days, and display the statistical result in real time.
The embodiment of the invention further provides a water heater tank yield statistical device with a model identification function, which comprises:
a data acquisition module: configuring a Hall current sensor and a voltage sensor for the welding machine, wherein the circular ring of the Hall current sensor is sleeved on a cable at the current output end of the welding machine, and the Hall current sensor detects the current of a welding loop of the welding machine; the voltage inductor is connected with a power supply of the welding machine in parallel and used for detecting the voltage of a main loop of the welding machine; the Hall current sensor and the voltage sensor simulate the detected data into weak current analog signals, and the Internet of things gateway decodes the weak current analog signals to obtain current and voltage data; using the decoded current data, voltage data and gas flow data as water heater liner welding process data, wherein the process data are time sequence data;
the welding machine state determination module: dividing the process data of the water heater inner container into a plurality of process data sections, shaping the current and voltage time sequence data in each process data section, and determining the welding machine state corresponding to each process data section based on the processed current data and voltage data;
an initialization module: setting a variable F, S, T, wherein F is used for marking whether arcing is performed, S is used for marking an arcing time point, T is used for marking the total welding time, the initial value of the variable F is false, the initial value of S is-1, and the initial value of T is-1;
a judging module: the method comprises the steps that whether the states of the welding machines corresponding to all process data sections are counted is judged, and if yes, a counting module is triggered; if not, acquiring a welder state corresponding to the process data section which is not subjected to statistics according to the time sequence, and triggering a state statistics module;
a state statistics module: setting a variable F to be true if the state of the welding machine corresponding to the non-counted process data segment is an arc starting welding stage, and setting a variable S to be a time point corresponding to an arc starting position in the process data segment; a triggering judgment module;
if the welding machine state corresponding to the non-counted process data segment is a standby state or a welding state, the variable value is not changed; a triggering judgment module;
if the state of the welding machine corresponding to the non-counted process data segment is an arc-ending time segment, if the value of the variable F is true, acquiring a time point corresponding to an arc-ending position in the process data segment, taking the difference value between the time point corresponding to the arc-ending position and the variable S as the total welding time length, and setting the variable T as the total welding time length;
if the total welding time is less than 20 seconds, the total number of the tank bodies is not counted, and an initialization module is triggered;
if the total welding time is more than or equal to 20 seconds, adding 1 to the total number of the tank bodies in the database, recording the tank body identification of the newly counted tank body and the total welding time corresponding to the tank body identification, and triggering an initialization module;
a statistic module: the method comprises the steps that all tank body identifications recorded in a database and total welding time corresponding to the tank body identifications are obtained, and the tank bodies with the total welding time difference within 2 seconds are identified as water heater tank bodies of the same type; and counting and displaying the number of the water heater tank bodies of each model and the identification of the water heater tank bodies of each model.
The embodiment of the invention further provides a water heater tank yield statistical system with a model identification function, which comprises:
a processor for executing a plurality of instructions;
a memory to store a plurality of instructions;
wherein the instructions are used for being stored by the memory and loaded and executed by the processor to perform the statistical method for the production of the water heater tank with the model identification function.
The embodiment of the invention further provides a computer readable storage medium, wherein a plurality of instructions are stored in the storage medium; the instructions are used for loading and executing the statistical method for the production of the water heater tank with the model identification function by the processor.
It should be noted that the embodiments and features of the embodiments may be combined with each other without conflict.
In the embodiments provided in the present invention, it should be understood that the disclosed system, apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one logical division, and there may be other divisions in actual implementation, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional unit.
The integrated unit implemented in the form of a software functional unit may be stored in a computer readable storage medium. The software functional unit is stored in a storage medium and includes several instructions to enable a computer device (which may be a personal computer, a physical machine server, or a network cloud server, etc., and needs to install a Ubuntu operating system) to perform some steps of the method according to various embodiments of the present invention. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.
The above description is only a preferred embodiment of the present invention, and is not intended to limit the present invention in any way, and any simple modification, equivalent change and modification made to the above embodiment according to the technical spirit of the present invention are still within the scope of the technical solution of the present invention.
Claims (10)
1. A statistical method for the yield of a water heater tank with a model identification function is characterized by comprising the following steps:
step S101: configuring a Hall current sensor and a voltage sensor for a welding machine, wherein the circular ring of the Hall current sensor is sleeved on a cable at the current output end of the welding machine, and the Hall current sensor detects the current of a welding loop of the welding machine; the voltage inductor is connected with a power supply of the welding machine in parallel and used for detecting the voltage of a main loop of the welding machine; the Hall current sensor and the voltage sensor simulate the detected data into weak current analog signals, and the Internet of things gateway decodes the weak current analog signals to obtain current and voltage data; using the decoded current data, voltage data and gas flow data as water heater liner welding process data, wherein the process data are time sequence data;
step S102: dividing the process data of the water heater inner container into a plurality of process data sections, shaping the current and voltage time sequence data in each process data section, and determining the welding machine state corresponding to each process data section based on the processed current data and voltage data;
step S103: setting a variable F, S, T, wherein F is used for marking whether arcing is performed, S is used for marking an arcing time point, T is used for marking the total welding time, the initial value of the variable F is false, the initial value of S is-1, and the initial value of T is-1;
step S104: judging whether the states of the welding machines corresponding to all the process data sections are counted up, if so, entering the step S106; if not, acquiring a welder state corresponding to the process data section which is not subjected to statistics according to the time sequence, and entering the step S105;
step S105: if the welder state corresponding to the non-counted process data segment is an arc starting welding stage, setting a variable F to be true, and setting a variable S to be a time point corresponding to an arc starting position in the process data segment; entering step S104;
if the welding machine state corresponding to the non-counted process data segment is a standby state or a welding state, the variable value is not changed; entering step S104;
if the state of the welding machine corresponding to the non-counted process data segment is an arc-ending time segment, if the value of the variable F is true, acquiring a time point corresponding to an arc-ending position in the process data segment, taking the difference value between the time point corresponding to the arc-ending position and the variable S as the total welding time length, and setting the variable T as the total welding time length;
if the total welding time is less than 20 seconds, the total number of the tank bodies is not counted, and the step S103 is carried out;
if the total welding time is longer than or equal to 20 seconds, adding 1 to the total number of the tank bodies in the database, recording the tank body identification of the newly counted tank body and the total welding time corresponding to the tank body identification, and entering the step S103;
step S106: acquiring all tank identifications recorded in a database and total welding time corresponding to the tank identifications, and identifying the tanks with the total welding time difference within 2 seconds as water heater tanks of the same model; and counting and displaying the number of the water heater tank bodies of each model and the identification of the water heater tank bodies of each model.
2. The method of claim 1, wherein the step S102: dividing the process data of the water heater inner container welding into a plurality of process data sections, shaping the current and voltage time sequence data in each process data section, and determining the welding machine state corresponding to each process data section based on the processed current data and voltage data, comprising the following steps:
step S1021: dividing the process data of the welding of the inner container of the water heater into a plurality of process data sections by taking 2 seconds as a unit;
step S1022: shaping the current and voltage time sequence data in each process data segment; the shaping treatment is as follows:
carrying out peak clipping and valley filling on original current and voltage time sequence data in a process data section by utilizing mean filtering, and specifically, selecting a plurality of sampling points uniformly for the process data section, taking three adjacent sampling points as a group, and dividing the sampling points of the process data section into a plurality of groups; for each group, calculating the average value of the three sampling points in the group, and replacing the original current and voltage time sequence data in the corresponding process data section of the group with the average value of the three sampling points in the group;
step S1023: for each shaped process data segment, the following operations are executed:
acquiring current and voltage time sequence data after the shaping processing of the process data segment, adding the processed current and voltage time sequence data corresponding to the same time point, taking the added result as an electric signal, and obtaining an electric signal sequence according to a time sequence;
for each electric signal in the electric signal sequence, judging whether the electric signal is greater than a welding threshold value, and if the electric signal is greater than or equal to the welding threshold value, updating the electric signal to be 1; if the current value is less than the welding threshold value, updating the electric signal to be 0;
after all the electric signals of the electric signal sequence are processed, splicing the updated electric signals according to the time sequence to generate updated time sequence data of the process data segment, wherein the updated time sequence data is time sequence data consisting of 0 and 1; the updated time sequence data of the process data segment are subjected to derivation, namely the position derivation result which is increased from 0 to 1 is 1, and the position derivation result which is decreased from 1 to 0 is-1; summing the results after the derivation to obtain a final summation result of the process data section;
if the final summation result of the process data segment is 0, determining that the state of the welding machine corresponding to the process data segment is a standby state or a welding state; if the final summation result of the process data segment is greater than or equal to 1, determining that the state of the welding machine corresponding to the process data segment is an arc starting welding stage; and if the final summation result of the process data segment is less than or equal to-1, determining that the state of the welding machine corresponding to the process data segment is an arc-closing time segment.
3. The method of claim 2, wherein the welding threshold is 10, i.e., welding is considered to be in progress when the sum of the current and voltage is greater than 10, and standby is considered to be in progress otherwise.
4. The method according to claim 3, wherein in step S106, the database can store data for a certain period of time, aggregate statistics are performed on the data in units of days, and the statistics are displayed in real time.
5. A water heater tank yield statistics device with model recognition function, its characterized in that device includes:
a data acquisition module: configuring a Hall current sensor and a voltage sensor for the welding machine, wherein the circular ring of the Hall current sensor is sleeved on a cable at the current output end of the welding machine, and the Hall current sensor detects the current of a welding loop of the welding machine; the voltage inductor is connected with a power supply of the welding machine in parallel and used for detecting the voltage of a main loop of the welding machine; the Hall current sensor and the voltage sensor simulate the detected data into weak current analog signals, and the Internet of things gateway decodes the weak current analog signals to obtain current and voltage data; using the decoded current data, voltage data and gas flow data as water heater liner welding process data, wherein the process data are time sequence data;
the welding machine state determination module: dividing the process data of the water heater inner container into a plurality of process data sections, shaping the current and voltage time sequence data in each process data section, and determining the welding machine state corresponding to each process data section based on the processed current data and voltage data;
an initialization module: setting a variable F, S, T, wherein F is used for marking whether arcing is performed, S is used for marking an arcing time point, T is used for marking the total welding time, the initial value of the variable F is false, the initial value of S is-1, and the initial value of T is-1;
a judging module: the method comprises the steps that whether the states of the welding machines corresponding to all process data sections are counted is judged, and if yes, a counting module is triggered; if not, acquiring a welder state corresponding to the process data section which is not subjected to statistics according to the time sequence, and triggering a state statistics module;
a state statistics module: setting a variable F to be true if the state of the welding machine corresponding to the non-counted process data segment is an arc starting welding stage, and setting a variable S to be a time point corresponding to an arc starting position in the process data segment; a triggering judgment module;
if the welding machine state corresponding to the non-counted process data segment is a standby state or a welding state, the variable value is not changed; a triggering judgment module;
if the state of the welding machine corresponding to the non-counted process data segment is an arc-ending time segment, if the value of the variable F is true, acquiring a time point corresponding to an arc-ending position in the process data segment, taking the difference value between the time point corresponding to the arc-ending position and the variable S as the total welding time length, and setting the variable T as the total welding time length;
if the total welding time is less than 20 seconds, the total number of the tank bodies is not counted, and an initialization module is triggered;
if the total welding time is more than or equal to 20 seconds, adding 1 to the total number of the tank bodies in the database, recording the tank body identification of the newly counted tank body and the total welding time corresponding to the tank body identification, and triggering an initialization module;
a statistic module: the method comprises the steps that all tank body identifications recorded in a database and total welding time corresponding to the tank body identifications are obtained, and the tank bodies with the total welding time difference within 2 seconds are identified as water heater tank bodies of the same type; and counting and displaying the number of the water heater tank bodies of each model and the identification of the water heater tank bodies of each model.
6. The apparatus of claim 5, wherein the welder status determination module comprises:
cutting the submodule: the method comprises the steps that process data for welding the inner container of the water heater are divided into a plurality of process data sections by taking 2 seconds as a unit;
a shaping processing submodule: the shaping device is configured to shape the current and voltage time sequence data in each process data segment; the shaping treatment is as follows:
carrying out peak clipping and valley filling on original current and voltage time sequence data in a process data section by utilizing mean filtering, and specifically, selecting a plurality of sampling points uniformly for the process data section, taking three adjacent sampling points as a group, and dividing the sampling points of the process data section into a plurality of groups; for each group, calculating the average value of the three sampling points in the group, and replacing the original current and voltage time sequence data in the corresponding process data section of the group with the average value of the three sampling points in the group;
a signal processing submodule: the method is configured to execute the following operations for each shaped process data segment:
acquiring current and voltage time sequence data after the shaping processing of the process data segment, adding the processed current and voltage time sequence data corresponding to the same time point, taking the added result as an electric signal, and obtaining an electric signal sequence according to a time sequence;
for each electric signal in the electric signal sequence, judging whether the electric signal is greater than a welding threshold value, and if the electric signal is greater than or equal to the welding threshold value, updating the electric signal to be 1; if the current value is less than the welding threshold value, updating the electric signal to be 0;
after all the electric signals of the electric signal sequence are processed, splicing the updated electric signals according to the time sequence to generate updated time sequence data of the process data segment, wherein the updated time sequence data is time sequence data consisting of 0 and 1; the updated time sequence data of the process data segment are subjected to derivation, namely the position derivation result which is increased from 0 to 1 is 1, and the position derivation result which is decreased from 1 to 0 is-1; summing the results after the derivation to obtain a final summation result of the process data section;
if the final summation result of the process data segment is 0, determining that the state of the welding machine corresponding to the process data segment is a standby state or a welding state; if the final summation result of the process data segment is greater than or equal to 1, determining that the state of the welding machine corresponding to the process data segment is an arc starting welding stage; and if the final summation result of the process data segment is less than or equal to-1, determining that the state of the welding machine corresponding to the process data segment is an arc-closing time segment.
7. The apparatus of claim 6, wherein the welding threshold is 10, i.e., welding is considered to be in progress when the sum of the current and voltage is greater than 10, and standby is considered to be in progress otherwise.
8. The apparatus of claim 7, wherein the statistics module and the database are capable of storing data for a certain period of time, performing aggregate statistics on the data in units of days, and displaying the statistics in real time.
9. A computer-readable storage medium having stored therein a plurality of instructions; the plurality of instructions for being loaded by a processor and for performing the method of any one of claims 1-4.
10. A computer-readable storage medium having stored therein a plurality of instructions; the plurality of instructions for being loaded by a processor and for performing the method of any one of claims 1-4.
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