A gas flow sensor chip for welding abnormality detection and a detection method thereof

Abstract

The present application relates to the technical field of airflow sensor, and particularly relates to a welding abnormality detection airflow sensor chip and a detection method thereof, which comprises: a basic global circuit, which provides reference voltage, bias current and clock signal for each module of the chip; a capacitor frequency conversion circuit, which is connected with the SE end at the input end and connected with the core logic circuit and the selector at the output end, converts the capacitor change into a frequency signal; the core logic circuit, which is used for comparing the frequency with the threshold value, outputs the control signal to the driving control; a virtual welding judgment circuit, which is embedded in the core logic circuit, periodically records and compares the initial frequency and the real-time frequency, accumulates the abnormal number of times to trigger the LED alarm; and a mode judgment logic circuit, which responds to the continuous square wave signal of 10 mu S of the LED end input, controls the selector to directly pass the frequency signal to the LED end. The present application has the beneficial effect that the welding abnormality can be detected more easily without increasing the cost, changing the existing chip pin distribution and the microphone circuit board layout.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of airflow sensor, in particular to an airflow sensor chip for welding abnormality detection and a detection method thereof. BACKGROUND

[0002] The airflow sensor chip is usually embedded in a microphone, and after assembly, the signal input pin of the chip is wrapped inside the microphone. It is difficult to determine the welding abnormality through simple test, which may cause the microphone to be mistakenly started and the time of occurrence is indefinite, bringing great difficulty to the abnormality troubleshooting.

[0003] In the prior art, the function problem caused by welding abnormality cannot be determined and detected through simple test, and the occurrence time of the microphone mistakenly started caused by welding abnormality is indefinite, and the test time of the microphone product is very limited, which brings considerable difficulty to the abnormality troubleshooting. SUMMARY

[0004] In view of the deficiencies of the prior art, the present application provides an airflow sensor chip for welding abnormality detection and a detection method thereof, which can detect welding abnormality more easily without increasing cost, changing the existing chip pin distribution and microphone circuit board layout.

[0005] The technical scheme of the present application is as follows: an airflow sensor chip for welding abnormality detection, comprising:

[0006] A basic global circuit provides reference voltage, bias current and clock signal for each module of the chip;

[0007] A capacitor frequency conversion circuit is connected to the SE end at the input end and connected to the core logic circuit and the selector at the output end, which converts the change of the capacitor into a frequency signal;

[0008] A core logic circuit is used to compare the frequency with the threshold value and output a control signal to the driving control;

[0009] A virtual welding determination circuit is embedded in the core logic circuit, which periodically records and compares the initial frequency and real-time frequency, and triggers the LED alarm when the cumulative abnormality number reaches a certain threshold value;

[0010] A mode determination logic circuit responds to the 10μS continuous square wave signal input from the LED end, and controls the selector to directly pass the frequency signal to the LED end.

[0011] As a preferred scheme of the present application, it further comprises a LORA module for transmitting the frequency value and the abnormality number to a remote terminal.

[0012] As a preferred scheme of the present application, the virtual welding determination circuit records the frequency abnormality number through an accumulator, and when the cumulative number exceeds a certain threshold value, the LED end flashes to alarm, and the type of pin fracture or poor contact is distinguished.

[0013] As a preferred scheme of the present application, the LED driving module cooperates with the mode determination logic circuit to filter the frequency offset anomaly according to a preset experience threshold when the SE end leaks electricity.

[0014] As a preferred scheme of the present application, the protection circuit integrates overcurrent, overtemperature and short circuit detection functions, and the abnormal state is monitored in real time through the power supply sampling feedback module and the output sampling feedback module.

[0015] As a preferred scheme of the present application, the square wave signal output by the capacitor frequency conversion circuit is output to the LED end after frequency division processing.

[0016] As a preferred scheme of the present application, the charging management module starts battery charging when the voltage at the VCC end is higher than the set threshold, and controls the charging state in linkage with the core logic circuit.

[0017] A detection method of a gas flow sensor chip for welding anomaly detection, comprising the following steps:

[0018] S1, complete the assembly of the microphone and the welding of the chip to the circuit board, or embed the circuit board in the microphone structure;

[0019] S2, power-on self-test, verify the connection state of the VDD end, the OUT end and the LED end, and switch to the input mode after the LED end flashes;

[0020] S3, input a continuous square wave signal of 10us period through the LED end to test the SE end connection anomaly;

[0021] S4, the virtual welding determination circuit periodically compares the initial frequency with the real-time frequency, and triggers the LED end alarm when the cumulative number of threshold values exceeds.

[0022] As a preferred scheme of the present application, in S2, multi-modal detection is performed:

[0023] In the power-on self-test stage, a 1kHz high-low level waveform is input to the LED end to verify the output waveform integrity;

[0024] In the standing monitoring stage, the LED is flashed n times or n-1 times to distinguish the virtual welding type.

[0025] As a preferred scheme of the present application, in S3, the mutual information feature construction algorithm is used to extract the time sequence correlation feature of the sensor signal, and a dynamic frequency threshold model is constructed, and the anomaly is determined when the frequency deviation exceeds ±10% and lasts for several update periods.

[0026] The present application has the following advantages:

[0027] 1. In the application, the chip is placed in the microphone, and through the chip pin multiplexing technology, the frequency square wave signal converted by the chip input end capacitor is directly output from the LED port;

[0028] 2. In the application, the chip has a built-in input pin virtual soldering determination circuit, which records the frequency initial value converted by the input pin after power-on, and periodically compares the existing frequency value with the initial value; when the frequency value changes more than the set threshold and lasts for the initial value update duration, the abnormal occurrence number is recorded, and when the cumulative abnormal number exceeds the set threshold, the alarm is triggered;

[0029] 3. In the application, the soldering abnormality can be detected more easily without changing the existing chip pin distribution and microphone circuit board layout, so that the microphone factory abnormality can be well excluded without increasing the cost. BRIEF DESCRIPTION OF DRAWINGS

[0030] Figure 1 It is a schematic diagram of the chip and peripheral application circuit structure of the application;

[0031] Figure 2 It is a schematic diagram of the chip of the application;

[0032] Figure 3 It is a state diagram of the virtual soldering detection function in the chip of the application;

[0033] Figure 4 It is a flow chart of the chip detection method of the application;

[0034] Figure 5 It is a state diagram of the chip detection method of the application;

[0035] In the figure: 100, chip; 101, air flow sensor; 102, light emitting diode; 103, capacitor; 104, VDD end; 105, VCC end; 106, GND end; 201, basic global circuit; 202, capacitor frequency conversion circuit; 203, charge management module; 204, core logic circuit; 205, virtual soldering determination circuit; 206, protection circuit; 207, power supply sampling feedback module; 208, driving control; 209, output sampling feedback module; 210, LED driving module; 211, selector; 212, mode determination logic circuit; 213, switch tube. DETAILED DESCRIPTION

[0036] To make the technical problems solved by the present invention, the technical solutions adopted, and the technical effects achieved clearer, the technical solutions of the embodiments of the present invention will be further described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0037] Example 1:

[0038] like Figures 1 to 3 As shown, a gas flow sensor chip 101 for detecting welding anomalies includes: VCC terminal 105, VDD terminal 104, SE terminal, OUT terminal, LED terminal and GND terminal 106.

[0039] Connect the VCC terminal 105 to the charging port;

[0040] VDD terminal 104 connects to the power supply;

[0041] The OUT terminal is used to connect the load resistor;

[0042] A capacitor 103 is connected between the VDD terminal 104 and the GND terminal 106 to reduce battery voltage fluctuations during operation.

[0043] A light-emitting diode is connected between the LED terminal and the GND terminal 106 to display the working status of the chip 100.

[0044] An airflow sensor 101 is connected between the SE terminal and the GND terminal 106 to convert airflow changes into capacitance changes of the capacitor 103 and input them into the chip 100.

[0045] In this embodiment, the airflow sensor 101 chip 100 is provided with a VCC terminal 105, a VDD terminal 104, an SE terminal, an OUT terminal, an LED terminal, and a GND terminal 106. The VCC terminal 105 is used to connect to the charging interface. The airflow sensor 101 is connected across the SE terminal and the GND terminal 106. The LED terminal is connected to the positive terminal of the light-emitting diode. The GND terminal 106 is connected to the negative terminal of the LED terminal.

[0046] In this embodiment, the chip 100 is placed in the microphone, and the metal diaphragm in the microphone is equivalent to the capacitor 103 sensor. The change of the capacitor 103 caused by the air pressure makes the frequency of the oscillator at the SE end also change accordingly. If the SE end is connected abnormally, the frequency at the SE end will also deviate from the normal range, or even deviate greatly. The SE port is wrapped and cannot be tested by the instrument to the frequency at this place. Even if the SE port is exposed outside the microphone, when the probe of the test instrument contacts the SE end solder point, the frequency will change due to the introduction of an additional capacitor 103. The signal at this place is amplified by the internal circuit of the chip 100 into a square wave signal, or passed through a frequency division process, and then output to the LED end. The square wave signal at the LED end is tested to the frequency at the SE port.

[0047] The core module of the airflow sensor 101 chip 100 includes: a basic global circuit 201, a core logic circuit 204, a charge management module 203, a capacitor frequency conversion circuit 202, a drive control 208, a MOS switch, a power supply sampling feedback module 207, an output sampling feedback module 209, a protection circuit 206, an LED drive module 210, a selector 211, a mode determination logic circuit 212, and a virtual welding determination circuit 205.

[0048] The basic global circuit 201 is connected with each module in the chip 100, and provides a reference voltage, a bias current, an enable signal, and a clock signal for each module of the chip 100.

[0049] The capacitor frequency conversion circuit 202 is used to convert the electrical characteristics of the airflow sensor 101 into a frequency, and the input end is connected to the SEN end of the chip 100, and the output end is connected to the core logic circuit 204 and the selector 211.

[0050] The core logic circuit 204 is connected to the capacitor frequency conversion circuit 202, the charge management module 203, the protection circuit 206, the drive control 208, and the selector 211. The main functions of the core logic circuit 204 include:

[0051] The frequency change is compared with the threshold frequency to determine whether the switch tube 213 is turned on.

[0052] The control signal is output to the drive control 208 after the signals input by each unit circuit are comprehensively judged.

[0053] The drive control 208 is connected to the input end of the MOS switch and the output end of the core logic circuit 204. The source and drain of the MOS switch are respectively connected to the VDD end 104 and the OUT end. The processing result of the core logic circuit 204 is output to the drive control 208. The output end of the drive control 208 is connected to the gate of the switch tube 213, i.e. the input end of the switch tube 213, so as to control the switch tube 213.

[0054] The charging management module 203 is configured to detect and determine whether to charge the battery when the voltage of the VCC terminal 105 is higher than a set threshold value, and connect the VCC terminal 105 and the core logic circuit 204.

[0055] The protection circuit 206 is configured to output the detected overcurrent signal, overtemperature signal and short-circuit state to the core logic circuit 204, and connect the power supply sampling feedback module 207 and the output sampling feedback module 209 to the core logic circuit 204.

[0056] The LED driving module 210 is configured to control the opening and closing and brightness state of the LED terminal, and connect the LED terminal, the selector 211 and the mode determination logic circuit 212.

[0057] The mode determination logic circuit 212 is configured to control the selector 211 to directly connect the waveform of the capacitor frequency conversion circuit 202 to the LED driving module 210 and drive the LED terminal when a specific waveform is input from the LED terminal, and connect the selector 211, the LED terminal and the LED driving module 210. If the SE terminal of the chip 100 is abnormally connected, such as open circuit or open circuit, the output frequency will deviate from the normal value, and the problem source of the SE port can be clearly located. If the SE terminal of the chip 100 leaks due to excessive use of flux, the frequency output from the LED terminal will also deviate from the normal value to a certain extent, and the threshold value can be set by experience to screen such abnormalities. If the chip 100 and the microphone have not appeared abnormal for a short time after assembly, but have experienced transfer transportation or SE terminal abnormality after use. Such abnormality is identified by the false soldering determination circuit 205, and the LED terminal flashes to alarm.

[0058] The false soldering determination circuit 205 is embedded in the core logic circuit 204 and connected to the selector 211. After power-on, the initial value of the frequency is recorded, and the real-time frequency is compared with the initial value periodically. When the frequency change is greater than the set threshold value and exceeds the initial value update time, the false soldering caused by the disconnection action occurs once. The number of times of the event is recorded by the accumulator, and when the number of times is greater than the set number of times, it is considered that the microphone has the false soldering caused by the disconnection and connection abnormality, and the LED terminal alarm is triggered.

[0059] Embodiment two

[0060] As shown in Figure 4 and Figure 5 , a detection method of a welding abnormality detection airflow sensor 101 chip, comprising the following steps:

[0061] S1, microphone assembly and chip 100 welding;

[0062] S2, port self-checking and function verification;

[0063] S3, detecting the connection state of the SE end;

[0064] S4, dynamic determination of false soldering and alarm.

[0065] In step S1, the microphone assembly and the chip 100 are soldered. Specifically, the microphone assembly and the chip 100 are soldered to a circuit board, or the circuit board is embedded in the microphone structure.

[0066] In step S2, port self-checking and function verification. Specifically, after power-on, the chip 100 automatically performs voltage detection, and if normal, triggers the LED end to flash once; the connection state of the VDD end 104, the OUT end and the LED end can be verified through load insertion and removal test. After the LED end flashing is completed, the driving MOS tube is closed, and at this time the LED port can be switched to input mode.

[0067] In step S3, the connection state of the SE end is detected. Specifically, a specific square wave signal is input through the LED end, for example, 10 continuous waveforms with a period of 10μS, to trigger the frequency pass-through mode, that is, the mode determination logic circuit 212 in the chip 100, so that the output of the capacitor frequency conversion circuit 202 is directly connected to the LED end. The frequency output by the LED end is tested, if the SE end is open or short, the frequency deviates significantly from the normal range, and the problem source is located in the SE end; if there is leakage, for example, residual flux, the frequency deviates slightly, and whether it is abnormal can be judged by a preset threshold. If the SE end of the chip 100 is connected abnormally, such as open circuit or open circuit, the output frequency will deviate far from the normal value, so the problem source can be clearly located in the SE port; if the chip 100 has SE end leakage caused by excessive use of flux, the frequency output from the LED end will also deviate from the normal value to a certain extent, and the threshold can be set by experience to screen such abnormalities.

[0068] In step S4, dynamic determination of false soldering and alarm. Specifically, after the microphone is powered on and left standing, the false soldering determination circuit 205 periodically compares the real-time frequency with the initial recorded value, and triggers the LED end to flash when the cumulative number of times exceeds the threshold. The false soldering determination circuit 205 is embedded in the core logic module, and the dynamic monitoring is realized by accumulating the number of abnormal events, which effectively identifies intermittent false soldering problems after transportation or use. After power-on, the initial value of the frequency is recorded, and the real-time frequency is compared with the initial value periodically, when the frequency change is greater than the set threshold and exceeds the initial value update time, it is recorded that the disconnection action caused by false soldering occurs once. The number of times of this event is recorded by the accumulator, and when it is greater than the set number of times, it is considered that the microphone has false soldering caused by intermittent disconnection and connection, and the LED end is triggered to alarm.

[0069] In a possible embodiment, a dynamic frequency threshold determination is performed. A mutual information feature construction algorithm is used to extract the time series correlation features of the sensor output signal, a dynamic frequency threshold model is constructed, and the false solder joint detection accuracy is improved. The real-time frequency is periodically compared with the initial frequency value. When the deviation exceeds the threshold ± 10% and lasts for 3 update periods, an abnormal record is triggered.

[0070] In a possible embodiment, a multi-modal detection mechanism is performed. In the power-on self-test stage, the high and low level waveforms (frequency 1 kHz) are input through the LED end to test the output waveform integrity and determine the soldering state of the SE end. In the static monitoring stage, the microphone is powered on and left for 30 seconds. The LED end flashes, for example, 3 times fast or 2 times slow, to distinguish the false solder joint type, pin breakage or poor contact.

[0071] In a possible embodiment, a LORA module is integrated to transmit the detection data to a remote terminal, support real-time monitoring of the soldering state, and the detection data includes the frequency value and the number of abnormalities.

[0072] In the present application, the chip 100 is placed in the microphone. Through the pin multiplexing technology of the chip 100, the frequency square wave signal converted by the input end capacitor 103 of the chip 100 is directly output from the LED port. The chip 100 is built-in input pin false solder joint determination circuit 205. After power-on, the initial value of the frequency converted by the input pin is recorded, and the existing frequency value is periodically compared with the initial value. When the frequency value changes more than the set threshold and lasts for the initial value update time, the number of abnormal occurrences is recorded. When the cumulative number of abnormal occurrences exceeds the set threshold, an alarm is triggered.

[0073] Although the preferred embodiments of the present application have been described, those skilled in the art can make further changes and modifications to these embodiments once they know the basic inventive concept. Obviously, those skilled in the art can make various modifications and variations to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the present application, the present application also intends to include these modifications and variations.

Claims

1. A gas flow sensor chip for weld anomaly detection, characterized by, Comprise: Basic global circuit, for each module of the chip provides reference voltage, bias current and clock signal; Capacitor frequency conversion circuit, the input end is connected with SE end, the output end is connected with core logic circuit and selector, the capacitor change is converted into frequency signal; Core logic circuit, for comparing frequency and threshold, output control signal to drive control; False soldering determination circuit, embedded in the core logic circuit, periodically records and compares the initial frequency and real-time frequency, accumulates the number of abnormal times to trigger LED alarm; Mode determination logic circuit, in response to the input of the period 10 μS continuous square wave signal of LED end, control selector straight through frequency signal to LED end.

2. The gas flow sensor chip for welding abnormality detection according to claim 1, characterized by Also include: LORA module, for transmitting frequency value and abnormal times to remote terminal.

3. The gas flow sensor chip for welding abnormality detection according to claim 1, wherein False soldering determination circuit records frequency abnormal times through accumulator, when the cumulative number exceeds the set threshold, trigger LED end flicker alarm, and distinguish the type of pin fracture or poor contact.

4. The gas flow sensor chip for welding abnormality detection according to claim 1, wherein Also includes LED drive module, LED drive module and mode determination logic circuit work together, when SE end leakage, according to the preset experience threshold to filter frequency offset abnormal.

5. The gas flow sensor chip for welding abnormality detection according to claim 1, wherein Also includes protection circuit, power sampling feedback module and output sampling feedback module, protection circuit integrates overcurrent, overtemperature and short circuit detection function, through power sampling feedback module and output sampling feedback module real-time monitoring abnormal state.

6. The gas flow sensor chip for welding abnormality detection according to claim 1, wherein The square wave signal output by capacitor frequency conversion circuit is output to LED end after frequency division processing.

7. The gas flow sensor chip for welding abnormality detection according to claim 1, wherein Also includes charging management module, charging management module starts battery charging when VCC end voltage is higher than the set threshold, and links with core logic circuit to control charging state.

8. A detection method of a welding abnormality detection air flow sensor chip, which is applied to the welding abnormality detection air flow sensor chip according to any one of claims 1 to 7, characterized in that, Including the following steps: S1, complete the assembly of microphone and chip welding to the circuit board, or embed the circuit board into the microphone structure; S2, power-on self-test, verify VDD end, OUT end and LED end connection state, LED end flicker after switching to input mode; S3, through the LED end input period 10 μS continuous square wave signal, test SE end connection abnormal; S4, false soldering determination circuit periodically compares the initial frequency and real-time frequency, accumulates the number of times exceeding threshold to trigger LED end alarm.

9. The detection method of a gas flow sensor chip for welding abnormality detection according to claim 8, wherein In S2, multi-modal detection is performed: Power-on self-test stage, input 1kHz high-low level waveform to LED end, verify the integrity of output waveform; Static monitoring stage, through LED fast flashing n times or slow flashing n-1 times to distinguish false soldering type.

10. The method of claim 8, wherein the welding abnormality detection gas flow sensor chip is characterized by, In S3, mutual information feature construction algorithm is used to extract the time sequence correlation feature of sensor signal, and dynamic frequency threshold model is constructed, when the frequency deviation exceeds ±10% and lasts for several update periods, the abnormality is determined.

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