WO2021000798A1 - 多通道压电式3d打印喷头故障识别及状态监测***及方法 - Google Patents

多通道压电式3d打印喷头故障识别及状态监测***及方法 Download PDF

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WO2021000798A1
WO2021000798A1 PCT/CN2020/098572 CN2020098572W WO2021000798A1 WO 2021000798 A1 WO2021000798 A1 WO 2021000798A1 CN 2020098572 W CN2020098572 W CN 2020098572W WO 2021000798 A1 WO2021000798 A1 WO 2021000798A1
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Prior art keywords
nozzle
piezoelectric
circuit
signal
monitoring
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PCT/CN2020/098572
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English (en)
French (fr)
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王莉
胡航锋
王科科
卢秉恒
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西安交通大学
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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B29—WORKING OF PLASTICS; WORKING OF SUBSTANCES IN A PLASTIC STATE IN GENERAL
    • B29C—SHAPING OR JOINING OF PLASTICS; SHAPING OF MATERIAL IN A PLASTIC STATE, NOT OTHERWISE PROVIDED FOR; AFTER-TREATMENT OF THE SHAPED PRODUCTS, e.g. REPAIRING
    • B29C64/00—Additive manufacturing, i.e. manufacturing of three-dimensional [3D] objects by additive deposition, additive agglomeration or additive layering, e.g. by 3D printing, stereolithography or selective laser sintering
    • B29C64/30—Auxiliary operations or equipment
    • B29C64/386—Data acquisition or data processing for additive manufacturing
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B29—WORKING OF PLASTICS; WORKING OF SUBSTANCES IN A PLASTIC STATE IN GENERAL
    • B29C—SHAPING OR JOINING OF PLASTICS; SHAPING OF MATERIAL IN A PLASTIC STATE, NOT OTHERWISE PROVIDED FOR; AFTER-TREATMENT OF THE SHAPED PRODUCTS, e.g. REPAIRING
    • B29C64/00—Additive manufacturing, i.e. manufacturing of three-dimensional [3D] objects by additive deposition, additive agglomeration or additive layering, e.g. by 3D printing, stereolithography or selective laser sintering
    • B29C64/30—Auxiliary operations or equipment
    • B29C64/386—Data acquisition or data processing for additive manufacturing
    • B29C64/393—Data acquisition or data processing for additive manufacturing for controlling or regulating additive manufacturing processes
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B33—ADDITIVE MANUFACTURING TECHNOLOGY
    • B33Y—ADDITIVE MANUFACTURING, i.e. MANUFACTURING OF THREE-DIMENSIONAL [3-D] OBJECTS BY ADDITIVE DEPOSITION, ADDITIVE AGGLOMERATION OR ADDITIVE LAYERING, e.g. BY 3-D PRINTING, STEREOLITHOGRAPHY OR SELECTIVE LASER SINTERING
    • B33Y50/00—Data acquisition or data processing for additive manufacturing
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B33—ADDITIVE MANUFACTURING TECHNOLOGY
    • B33Y—ADDITIVE MANUFACTURING, i.e. MANUFACTURING OF THREE-DIMENSIONAL [3-D] OBJECTS BY ADDITIVE DEPOSITION, ADDITIVE AGGLOMERATION OR ADDITIVE LAYERING, e.g. BY 3-D PRINTING, STEREOLITHOGRAPHY OR SELECTIVE LASER SINTERING
    • B33Y50/00—Data acquisition or data processing for additive manufacturing
    • B33Y50/02—Data acquisition or data processing for additive manufacturing for controlling or regulating additive manufacturing processes

Definitions

  • the invention belongs to the field of advanced manufacturing technology, and specifically relates to a system and method for multi-channel piezoelectric 3D printing nozzle failure identification and status monitoring.
  • 3D printing is a revolutionary manufacturing method developed since the mid-1990s. It is based on the principle of material accumulation and molding, starting from the three-dimensional CAD model of the part, the model is discretized and sliced and layered, and then the two-dimensional data is manufactured layer by layer and finally accumulated into a three-dimensional entity to realize the workpiece forming and manufacturing.
  • Droplet ejection technology is widely used in 3D printing.
  • the nozzle is a precision device, it is prone to ejection failures such as over-limit driving voltage, high-viscosity plugging, and imbalance of ink supply pressure. This type of failure can only be performed under ink viewing equipment. It was discovered that it not only took a lot of time to repair the print head, but also seriously affected the print quality.
  • the above methods have the following problems: the specific fault type cannot be effectively identified, which is not conducive to taking corresponding measures; the detection can only be performed at a fixed location, which affects the detection efficiency.
  • the technical problem to be solved by the present invention is to provide a multi-channel piezoelectric 3D printing nozzle fault identification and status monitoring system and method for the above-mentioned shortcomings in the prior art, which can effectively identify the fault type and calculate the droplet speed, and improve the detection Accuracy, can be detected in the process of printing movement of the nozzle, not restricted by the position of the nozzle, greatly improving the flexibility of detection.
  • a multi-channel piezoelectric 3D printing nozzle fault identification and status monitoring system including a nozzle drive circuit, a multi-channel gating circuit, a piezoelectric signal acquisition circuit and a monitoring unit.
  • the nozzle drive circuit is used to provide a drive signal to make the piezoelectric nozzle eject ;
  • Multi-channel gating circuit is used to provide multi-channel alternate gating signals to realize piezoelectric nozzle multi-hole rotation monitoring;
  • piezoelectric signal acquisition circuit uses self-induction detection method to collect residual vibration signals in the piezoelectric nozzle flow channel cavity; monitoring unit Including driving voltage monitoring, liquid viscosity monitoring, ink supply pressure monitoring and droplet ejection speed calculation modules, used to monitor the working status of the piezoelectric nozzle.
  • the piezoelectric signal acquisition circuit includes a nozzle circuit and an equivalent circuit.
  • the equivalent circuit includes a voltage divider resistor R 2 and an equivalent capacitance C e of the nozzle.
  • the output signal V out of the capacitor terminal voltage V 2 and the capacitor terminal voltage V 1 in the nozzle circuit processed by the piezoelectric signal acquisition circuit is connected to the data acquisition system for outputting the final result.
  • the multi-channel gating circuit includes an equivalent circuit, a drive signal generator, a multi-channel gating switch and a multi-nozzle nozzle.
  • the piezoelectric signal acquisition circuit is divided into two paths, one of which is connected to the multi-channel gating switch for extraction
  • the nozzle capacitor terminal voltage in the nozzle circuit is connected to the remote terminal of the equivalent capacitor C ne in the equivalent circuit to extract the equivalent capacitor terminal voltage in the equivalent circuit;
  • the multi-channel strobe switch receives the strobe signal and compares it with the Orifice nozzle connection.
  • the equivalent circuit includes a voltage divider resistor R r and an equivalent capacitance C ne .
  • the self-induced voltage signal V n of the nth nozzle hole and the equivalent voltage signal V r of the equivalent circuit are processed by the piezoelectric signal acquisition circuit.
  • Another technical solution of the present invention is a multi-channel piezoelectric 3D printing nozzle failure identification and status monitoring method, using the multi-channel piezoelectric 3D printing nozzle failure identification and status monitoring system, using self-induction detection method
  • the residual vibration signal in the flow channel cavity of the piezoelectric nozzle is converted into a voltage signal for collection and analysis to obtain the corresponding characteristic parameters when the fault occurs.
  • the algorithm model between the ejection fault and the characteristic parameters and the droplet velocity and the characteristic parameters is established.
  • the characteristic parameters corresponding to each factor in the voltage monitoring, liquid viscosity monitoring, ink supply pressure monitoring, and droplet ejection speed calculation modules exceed the threshold, which indicates that a fault has occurred.
  • the driving voltage monitoring is judged by the sharp angle amplitude in the self-induction signal as the characteristic parameter.
  • the sharp angle amplitude is the first sharp-angle amplitude of the collected self-induction signal.
  • the nozzle is sprayed at a fixed orifice, and the piezoelectric signal acquisition circuit and data acquisition system are used to extract and collect the pressure wave signal in the piezoelectric nozzle channel cavity.
  • the nozzle driving voltage is too small, the droplet ejection speed is lower than the normal value or the driving voltage
  • the indicator light corresponding to the driving voltage lights up, indicating that the droplet ejection failure is caused by the voltage.
  • the liquid viscosity monitoring is judged by the damping ratio in the self-induction signal as a characteristic parameter.
  • the damping ratio is calculated from the attenuation damping ratio of the residual vibration at the tail of the collected self-induction signal.
  • the pressure wave signal in the channel cavity of the piezoelectric nozzle is extracted and collected by the piezoelectric signal acquisition circuit and data acquisition system.
  • the ink supply pressure monitoring is judged by the phase in the self-induction signal as a characteristic parameter, and the phase is calculated from the phase of the collected self-induction signal, and a selected nozzle is ejected through the nozzle drive circuit, using a piezoelectric signal
  • the acquisition circuit and data acquisition system extract and collect the pressure wave signal in the flow channel cavity of the piezoelectric nozzle.
  • the negative pressure of the ink supply pressure is too small, the nozzles will accumulate droplets and cannot be ejected or when the negative pressure of the ink supply pressure is too large, the ejection will be caused.
  • the indicator light corresponding to the ink supply pressure is on, indicating that the ejection failure of the droplet is caused by the pressure.
  • the droplet ejection velocity calculation scheme is calculated by the regression model.
  • a selected nozzle is ejected through the nozzle drive circuit, and the piezoelectric signal acquisition circuit and data acquisition system are used to detect the pressure wave in the piezoelectric nozzle flow channel.
  • the signal is extracted and collected.
  • the ejection condition is within the normal range, it indicates that it is in a normal ejection state.
  • the velocity value calculated by the regression model reflects the ejection velocity of the droplet.
  • the characteristic value judgment step is as follows:
  • the present invention has the following beneficial effects:
  • the present invention is a multi-channel piezoelectric 3D printing nozzle fault identification and status monitoring system. It adopts a time-sharing multiplexing detection scheme. By designing a multi-channel gating circuit to achieve multiple nozzles alternate detection, it greatly reduces the hardware cost and The power consumption of the circuit also guarantees the detection efficiency.
  • the detection circuit used can convert the tiny pressure wave signal in the flow channel of the piezoelectric nozzle into a self-induced voltage signal for extraction and analysis, which improves the detection accuracy and can print movement on the nozzle. In the process of detection, it is not restricted by the position of the nozzle, which greatly improves the flexibility of detection.
  • the overall size of the detection circuit is small, the piezoelectric effect of the piezoelectric nozzle is used, and no additional sensor is needed, which is convenient to install on the nozzle for monitoring. Further, the detection circuit can be packaged inside the nozzle to provide technical support for the manufacture of the piezoelectric nozzle .
  • the present invention also discloses a multi-channel piezoelectric 3D printing nozzle fault identification and status monitoring method.
  • the nozzle When the nozzle is ejected abnormally, it can simultaneously detect the driving voltage, liquid viscosity, ink supply pressure and other fault factors. When one or more factors cause an ejection failure, there are corresponding status indications, which can effectively identify the type of failure, which is helpful for users to take treatment measures in time; when the nozzle is ejecting normally, the droplet ejection speed can be calculated, which is convenient for users to optimize The ejection parameters make the droplet ejection speed control within a proper range.
  • the driving voltage by monitoring the magnitude of the driving voltage, it is directly judged whether there is an ejection failure caused by the driving voltage exceeding the limit, and the user is reminded to adjust the driving voltage. For example, when the ejection voltage is too low, the droplet velocity and volume will be too small due to insufficient driving force, which will affect the density of 3D printed parts. When the ejection voltage is too high, some micro-liquid will be generated around the droplets due to excessive driving force. Drip eventually reduces the resolution of 3D printed parts.
  • the user is reminded to use a liquid with a suitable viscosity for ejection. For example, when the liquid viscosity is too high, the nozzle will be blocked and cannot be ejected. When the liquid viscosity is too low, there will be a long liquid column at the tail of the main droplet, which will eventually cause droplets to spread on the surface of the printing medium.
  • the ink supply pressure by monitoring the ink supply pressure, it is directly judged whether there is an ejection failure caused by the abnormal ink supply pressure, and the user is reminded to adjust the ink supply pressure. For example, when the negative pressure of the ink supply pressure is too small, the droplets will be squeezed out and hang on the surface of the nozzle hole and finally fall on the printing medium to damage the printed surface. When the negative pressure of the ink supply pressure is too large, the air will be sucked into the nozzle hole. The inside makes the ejected droplets become chaotic.
  • the real-time velocity of the droplet is obtained through the calculation of the characteristic parameters. There is no need to move the nozzle to a specific position for observation, which saves measurement time and space, simplifies the measurement process, and allows users to monitor the results through real-time velocity. Adjust the corresponding process parameters to achieve the optimal control of the droplet velocity.
  • the status of each driving factor and the speed of the droplet are obtained by calculating each characteristic value and comparing and judging.
  • the corresponding status indicator will immediately light up to remind the user that the corresponding failure has occurred, and the monitoring process is efficient, The monitoring results are clear and easy to understand.
  • the present invention provides a multi-channel piezoelectric 3D printing nozzle failure identification and status monitoring system and method.
  • the self-induction detection method is used to extract the self-induction signal inside the nozzle without using additional sensors.
  • the characteristic parameters of the self-induction signal are calculated to determine the ejection state of the nozzle. It can effectively identify the fault type and cause, improve the monitoring accuracy, and facilitate the user to take effective measures; at the same time, no external sensor is required, which solves the inconvenience of sensor installation, and reduces the hardware cost through alternate monitoring; it can be monitored during the working process of the nozzle , It is not restricted by the position of the nozzle and improves the flexibility of monitoring.
  • Figure 1 is a schematic diagram of a piezoelectric signal acquisition circuit that converts the pressure wave signal in the flow channel of the piezoelectric nozzle into an electrical signal by means of self-induction;
  • Figure 2 is a schematic diagram of a multi-channel alternate monitoring circuit
  • Figure 3 is a graph of self-induction signals collected by a piezoelectric signal acquisition circuit and a data acquisition system
  • Figure 4 is a flow chart of nozzle spraying status monitoring
  • Figure 5 is a schematic diagram of condition monitoring based on regression model and algorithm development
  • Figure 6 is a monitoring effect diagram of the droplet velocity being too low due to insufficient drive voltage
  • Figure 7 is the monitoring effect diagram of the high liquid viscosity causing the droplet velocity to be too low
  • Figure 8 is a monitoring effect diagram of the droplets gathering on the surface of the nozzle hole due to the negative pressure of the ink supply pressure being too small.
  • a layer/element when referred to as being “on” another layer/element, the layer/element may be directly on the other layer/element, or there may be an intermediate layer/element between them. element.
  • the layer/element may be located “under” the other layer/element when the orientation is reversed.
  • the present invention provides a multi-channel piezoelectric 3D printing nozzle fault identification and status monitoring system and method.
  • the residual vibration signal in the piezoelectric nozzle flow channel cavity is converted into a voltage signal by means of self-induction detection.
  • the characteristic parameter corresponding to this kind of fault occurs. If the characteristic parameter exceeds the threshold value, it indicates that a fault has occurred. It is convenient to take corrective measures to judge the fault type through the indicator light.
  • the present invention can monitor the spraying status of the spraying head during the moving and printing process of the spraying head without being restricted by the position of the spraying head; at the same time, the present invention adopts a rotation monitoring method to realize multi-spouting hole monitoring. Condition monitoring greatly reduces hardware costs, improves detection efficiency and ensures the stability and reliability of the print head.
  • the present invention is a multi-channel piezoelectric 3D printing nozzle failure identification and status monitoring system, which includes a nozzle drive circuit, a multi-channel gating circuit, a piezoelectric signal acquisition circuit and a monitoring unit.
  • the nozzle drive circuit is used to provide drive signals to make pressure Electronic nozzle ejection;
  • multi-channel gating circuit is used to provide multi-channel alternate gating signals to realize the solution of piezoelectric nozzle multi-nozzle alternate monitoring;
  • piezoelectric signal acquisition circuit uses self-induction detection method to collect the residue in the piezoelectric nozzle flow channel Vibration signal; the monitoring unit is used to present the detection result of the piezoelectric nozzle to the user.
  • the piezoelectric signal acquisition circuit includes a nozzle circuit and an equivalent circuit.
  • the equivalent circuit includes a voltage divider resistor R 2 and an equivalent capacitance C e of the nozzle.
  • the nozzle circuit includes a voltage divider resistor R 1 and a static capacitance C of the nozzle.
  • the multi-channel gating circuit includes an equivalent circuit, a drive signal generator, a multi-channel gating switch and a multi-nozzle nozzle.
  • the piezoelectric signal acquisition circuit is divided into two paths, one of which is connected to the multi-channel gating switch. To extract the nozzle capacitor terminal voltage in the nozzle circuit, the other is connected to the remote terminal of the equivalent capacitor C ne in the equivalent circuit to extract the equivalent capacitor terminal voltage in the equivalent circuit; the multi-channel gating switch receives the strobe signal, And connect with multi-hole nozzle.
  • the equivalent circuit includes a voltage divider resistor R r and an equivalent capacitance C ne .
  • the self-induced voltage signal V n of the nth nozzle and the equivalent voltage signal V r of the equivalent circuit are processed by the piezoelectric signal acquisition circuit.
  • the output signal V nout is connected to the data acquisition system to output the final result;
  • t h is a single channel gating duration
  • t s is the time between adjacent channels gated
  • t h can be adjusted by setting the time of single-channel gating.
  • the monitoring unit includes driving voltage monitoring, liquid viscosity monitoring, ink supply pressure monitoring and droplet ejection speed calculation modules.
  • the working principle of the present invention is:
  • the piezoelectric material has a piezoelectric effect, which allows the piezoelectric plate to be used as a driver or a sensor in the nozzle system.
  • the piezoelectric plate When the piezoelectric plate is used as a sensor, its internal current includes the current generated by the charge and discharge effect and the current generated by the residual pressure wave through the piezoelectric effect.
  • the spraying state of the nozzle will affect the residual pressure wave and then the current inside the piezoelectric plate, so the current of the piezoelectric plate is collected to analyze the spraying state of the nozzle.
  • a multi-channel piezoelectric 3D printing nozzle fault identification and status monitoring method The residual vibration signal in the piezoelectric nozzle flow channel cavity is converted into a voltage signal by means of self-induction detection. Establish the algorithm model between the ejection faults and the characteristic parameters and the droplet velocity and the characteristic parameters.
  • the driving voltage monitoring, liquid viscosity monitoring, ink supply pressure monitoring and droplet ejection velocity calculation modules correspond to each factor
  • the characteristic parameter exceeds the set threshold, the warning light will be on.
  • the driving voltage monitoring scheme is judged by the sharp angle amplitude in the self-induction signal as the characteristic parameter.
  • the sharp angle amplitude is the first sharp angle amplitude of the collected self-induction signal.
  • the sharp angle amplitude exceeds the set value, When the threshold is set, it is considered that the driving voltage causes the injection failure;
  • the liquid viscosity monitoring program is judged by the damping ratio in the self-induction signal as a characteristic parameter.
  • the damping ratio is calculated from the attenuation damping ratio of the residual vibration at the tail of the collected self-induction signal.
  • the calculation method is the amplitude ratio of adjacent peaks or valleys. , When the damping ratio exceeds the set threshold, it is considered that the liquid viscosity has caused injection failure;
  • the ink supply pressure monitoring scheme is judged by the phase in the self-induction signal as a characteristic parameter.
  • the phase is calculated from the phase corresponding to the second-order frequency of the collected self-induction signal.
  • the ink supply pressure is considered to cause ejection. malfunction;
  • the calculation scheme of droplet ejection velocity is calculated by regression model.
  • the droplet ejection velocity is calculated by the regression model established between the characteristic parameters.
  • the regression model is based on experimental data fitting and is basically consistent with the kinetic model of the piezoelectric nozzle ejection process.
  • the experimental factors are driving voltage, liquid Viscosity, ink supply pressure, the dependent variable is the droplet velocity.
  • time domain sharp angle amplitude eigenvalues, residual vibration damping ratio eigenvalues, and frequency domain phase eigenvalues are normal, and the droplet velocity is calculated separately;
  • the eigenvalues of the amplitude of the sharp angles in the time domain, the eigenvalues of the residual vibration damping ratio, and the eigenvalues of the phase in the frequency domain are abnormal, which ends directly.
  • a selected nozzle is ejected through the nozzle drive circuit, and the piezoelectric signal acquisition circuit and data acquisition system are used to extract and collect the pressure wave signal in the piezoelectric nozzle flow channel cavity.
  • the nozzle drive voltage exceeds
  • the droplet ejection speed is lower than the normal value or the driving voltage is too large to produce satellite droplets around the main droplet
  • the voltage indicator light on the monitoring software interface is on, indicating that the droplet ejection failure is caused by voltage.
  • a selected nozzle is ejected through the nozzle drive circuit, and the piezoelectric signal acquisition circuit and data acquisition system are used to extract and collect the pressure wave signal in the piezoelectric nozzle flow channel. Too large causes the droplet ejection speed to be lower than the normal value or the droplet viscosity is too small to make the liquid column at the tail of the main droplet longer. At this time, the viscosity indicator on the monitoring software interface is on, indicating that the droplet ejection failure is caused by viscosity.
  • a selected nozzle is ejected through the nozzle drive circuit, and the piezoelectric signal acquisition circuit and data acquisition system are used to extract and collect the pressure wave signal in the piezoelectric nozzle flow channel cavity.
  • the ink supply pressure is negative
  • the nozzle hole has droplets that cannot be ejected, or when the negative pressure of the ink supply pressure is too large, and the bubbles in the nozzle hole cannot be ejected, the pressure indicator on the monitoring software interface will light up, indicating that the droplets are caused by pressure. Jet failure.
  • a selected nozzle is ejected through the nozzle drive circuit, and the piezoelectric signal acquisition circuit and data acquisition system are used to extract and collect the pressure wave signal in the piezoelectric nozzle flow channel cavity.
  • the indicator lights of each factor on the monitoring software interface are normal at this time, indicating that it is in the normal ejection state at this time.
  • the velocity value calculated by the regression model can be used to reflect the ejection velocity of the droplet.
  • the calculated value is basically the same as the actual value measured by the ink viewing device, indicating that the condition monitoring software can effectively calculate the droplet velocity.
  • a nozzle with 16 nozzles is sprayed in turn through a nozzle drive circuit and a multi-channel gating circuit, and a piezoelectric signal collection circuit is used to collect residual vibration signals in the flow channel cavity and calculate it by monitoring software
  • the droplet ejection velocity of each nozzle hole can be used to monitor the droplet velocity of multiple nozzle holes.
  • Figure 5 is a state monitoring software interface developed based on regression models and algorithms, including serial port configuration, sampling settings, waveform display, monitoring state result display and other modules. This interface can directly and effectively display the causes and causes of nozzle jet failure. The velocity of the droplets during normal ejection;
  • the left side of Figures 6 to 8 is the monitoring interface, and the black dot on the right is the real-time image of the droplet collected by the ink viewing device.
  • the droplet velocity can be measured for comparison and verification of the monitoring effect of the present invention.
  • the ink viewing device used is In the MiWatcher device of Hangzhou Mijie Company, the higher the position of the droplet, the lower the droplet velocity. When the droplet velocity is lower than the reference value, it is considered that an ejection failure has occurred.
  • the reference velocity in the present invention is set to 5m/s.
  • the droplet velocity measured by the ink viewing device is 2.88m/s, which is a fault state.
  • the indicator light corresponding to the viscosity of the liquid turns on, indicating a failure caused by the viscosity of the sprayed liquid;

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Abstract

一种多通道压电式3D打印喷头故障识别及状态监测***及方法，包括喷头驱动电路、多通道选通电路、压电信号采集电路及监测单元，喷头驱动电路用于提供驱动信号使压电喷头喷射；多通道选通电路用于提供多通道轮流选通信号实现压电喷头多喷孔轮流监测；压电信号采集电路利用自感应检测方式采集压电喷头流道腔体内的残余振动信号；监测单元包括驱动电压监测、液体粘度监测、供墨压力监测和液滴喷射速度计算模块，用于监测压电喷头工作状态。该***及方法能有效识别故障类型及产生原因，提高监测准确性，便于用户采用有效措施；同时无需外部传感器，通过轮流监测的方式降低了硬件成本；可在喷头工作过程中进行监测，提高监测灵活性。

Description

多通道压电式3D打印喷头故障识别及状态监测***及方法 【技术领域】
本发明属于先进制造技术领域，具体涉及一种多通道压电式3D打印喷头故障识别及状态监测***及方法。
【背景技术】
3D打印是从上世纪九十年代中期开始发展起来的一种革命性的制造方法。其基于材料累积成型的原理，从零件三维CAD模型出发，将模型进行离散化切片分层处理，然后将二维数据逐层制造最终累积成三维实体，实现工件成型制造。微滴喷射技术广泛应用在3D打印中，然而由于喷头属于精密器件，极易发生驱动电压超限、高粘堵头和供墨压力失衡等喷射故障，这类故障目前只能在观墨设备下被发现，不但需要大量的时间来维修喷头，而且严重了影响打印质量。
目前国内外对喷头喷射状态进行检测的研究有：
(1)韩国顺天乡大学利用压电喷头的自感应方式提取喷头流道腔体内的残余振动信号进行分析，采用方差的算法对喷头喷射状态进行检测，该方法通过单一算法特征参数实现喷射故障监测，对于有些喷射故障下特征参数重合混叠的情况无法有效识别出故障类型，也不能对液滴速度进行监测；
(2)杭州电子科技大学通过CCD高速相机进行墨滴喷射的图像采集，利用区域增长法来提取墨滴形态，并计算墨滴的速度和体积，该方法只能在特定位置对喷头进行检测，过程繁琐。
以上方法中存在如下问题：无法有效识别出具体故障类型，不利于采取对应措施；只能在固定位置进行检测，影响检测效率。
【发明内容】
本发明所要解决的技术问题在于针对上述现有技术中的不足，提供一种多通道压电式3D打印喷头故障识别及状态监测***及方法，能有效识别故障类型并计算液滴速度，提高检测准确性，能在喷头打印运动的过程中进行检测，不受喷头位置限制，大大提高了检测的灵活性。
为达到上述目的，本发明采用以下技术方案予以实现：
一种多通道压电式3D打印喷头故障识别及状态监测***，包括喷头驱动电路、多通道选通电路、压电信号采集电路及监测单元，喷头驱动电路用于提供驱动信号使压电喷头喷射；多通道选通电路用于提供多通道轮流选通信号实现压电喷头多喷孔轮流监测；压电信号采集电路利用自感应检测方式采集压电喷头流道腔体内的残余振动信号；监测单元包括驱动电压监测、液体粘度监测、供墨压力监测和液滴喷射速度计算模块，用于监测压电喷头工作状态。
具体的，压电信号采集电路包括喷头电路和等效电路，等效电路包括分压电阻R 2和喷头的等效电容C e，喷头电路包括分压电阻R 1和喷头的静态电容C p，且C p＝C e，R 1＝R 2，输入的驱动电压V in分两路，一路经电阻R 2和电容C e接地，另一路经电阻R 1和电容C p接地，等效电路中电容端电压V 2和喷头电路中电容端电压V 1经压电信号采集电路处理后的输出信号V out与数据采集***连接，用于输出最终结果。
具体的，多通道选通电路包括等效电路、驱动信号发生器、多通道选通开关和多喷孔喷头，压电信号采集电路分两路，一路与多通道选通开关连接，用于提取喷头电路中喷头电容端电压，另一路与等效电路中等效电容C ne的远地端连接，用于提取等效电路中等效电容端电压；多通道选通开关接收选通信号，并与多喷 孔喷头连接。
进一步的，等效电路包括分压电阻R r和等效电容C ne，第n个喷孔的自感应电压信号V n与等效电路的等效电压信号V r经过压电信号采集电路进行处理，处理后的输出信号V nout与数据采集***连接，用于输出最终结果；驱动信号发生器提供的输入电压V nin分两路，一路经被测量喷孔电路的分压电阻R n及喷孔电路后接地，用于使喷头喷射产生自感应信号V n，另一路经等效电路的分压电阻R r与等效电容C ne后接地，用于输出等效电压信号V r，且R r＝R n。
本发明的另一技术方案是，一种多通道压电式3D打印喷头故障识别及状态监测方法，利用所述的多通道压电式3D打印喷头故障识别及状态监测***，采用自感应检测方式将压电喷头流道腔体内的残余振动信号转化为电压信号进行采集分析后得到故障发生时对应的特征参数，建立喷射故障与特征参数以及液滴速度与特征参数之间的算法模型，当驱动电压监测、液体粘度监测、供墨压力监测和液滴喷射速度计算模块中各个因素对应的特征参数超过阈值则表明发生故障。
具体的，驱动电压监测由自感应信号中的尖角幅值作为特征参数进行判断，尖角幅值为采集到的自感应信号的第一个尖角幅值，通过喷头驱动电路对某一选定喷孔进行喷射，采用压电信号采集电路和数据采集***对压电喷头流道腔体内的压力波信号进行提取采集，当喷头驱动电压过小导致液滴喷射速度低于正常值或驱动电压过大使得主液滴周围产生卫星液滴时，驱动电压对应的指示灯亮起，表明是由电压导致的液滴喷射故障。
具体的，液体粘度监测由自感应信号中的阻尼比作为特征参数进行判断，阻尼比由采集到的自感应信号尾部的残余振动的衰减阻尼比计算所得，通过喷头驱 动电路对某一选定喷孔进行喷射，采用压电信号采集电路和数据采集***对压电喷头流道腔体内的压力波信号进行提取采集，当被喷射液体粘度过大导致液滴喷射速度低于正常值或液滴粘度很小使得主液滴尾部的液柱较长时，液体粘度对应的指示灯亮起，表明是由粘度导致的液滴喷射故障。
具体的，供墨压力监测由自感应信号中的相位作为特征参数进行判断，相位由采集到的自感应信号相位计算所得，通过喷头驱动电路对某一选定喷孔进行喷射，采用压电信号采集电路和数据采集***对压电喷头流道腔体内的压力波信号进行提取采集，当供墨压力负压过小时导致喷孔有液滴聚集无法喷射或当供墨压力负压过大导致喷孔内吸入气泡无法喷射时，供墨压力对应的指示灯亮起，表明是由压力导致的液滴喷射故障。
具体的，液滴喷射速度计算方案由回归模型计算获得，通过喷头驱动电路对某一选定喷孔进行喷射，采用压电信号采集电路和数据采集***对压电喷头流道腔体内的压力波信号进行提取采集，当喷射条件在正常范围内时，表明处于正常喷射状态，通过回归模型计算出的速度值反映液滴的喷射速度。
进一步的，其特征在于，特征值判断步骤如下：
S1、读取压电信号，依次对时域尖角幅值特征值、残余振动阻尼比特征值和频域相位特征值进行判断；
S2、当时域尖角幅值特征值、残余振动阻尼比特征值和频域相位特征值均正常时，计算液滴速度后结束；
S3、当时域尖角幅值特征值、残余振动阻尼比特征值和频域相位特征值中的任意一个产生异常时，直接结束。
与现有技术相比，本发明具有以下有益效果：
本发明一种多通道压电式3D打印喷头故障识别及状态监测***，采用分时复用的检测方案，通过设计多通道选通电路来实现多喷孔的轮流检测，大大降低了硬件成本及电路功耗，同时也保证了检测效率，所用的检测电路能将压电喷头流道腔体内的微小压力波信号转化为自感应电压信号进行提取分析，提高检测准确度，能在喷头打印运动的过程中进行检测，不受喷头位置限制，大大提高了检测的灵活性。
进一步的，检测电路整体尺寸小，利用压电喷头自身的压电效应，无需外加传感器，便于安装在喷头上进行监测，进一步可以将检测电路封装到喷头内部，为压电喷头的制造提供技术支撑。
本发明还公开了一种多通道压电式3D打印喷头故障识别及状态监测方法，在喷头非正常喷射时，能够同时对驱动电压、液体粘度、供墨压力等故障因素进行检测，当上述一种或多种因素导致喷射故障发生时，均有对应的状态指示反映，能有效识别出故障类别，有利于用户及时采取处理措施；在喷头正常喷射时能计算出液滴喷射速度，便于用户优化喷射参数使液滴喷射速度控制在合适范围内。
进一步的，通过监测驱动电压的大小来直接判断是否有驱动电压超限导致的喷射故障，提醒用户对驱动电压进行调整。例如，当喷射电压过小时，会因为驱动力不足导致液滴速度和体积均偏小影响3D打印零件的密度，当喷射电压过大时，会因为驱动力过大导致液滴周围产生部分微型液滴最终使得3D打印零件的分辨率降低。
进一步的，通过监测液体粘度的大小来直接判断是否有液体粘度不适导致的喷射故障，提醒用户采用合适粘度的液体进行喷射。例如，当液体粘度过大时会使喷头堵塞无法喷射，当液体粘度过小时会使得主液滴的尾部会有很长的液柱最 终使得打印介质表面产生液滴扩散。
进一步的，通过监测供墨压力的大小来直接判断是否有供墨压力异常导致的喷射故障，提醒用户对供墨压力进行调整。例如，当供墨压力负压过小时会使得液滴被挤出悬挂在喷孔表面最终掉落在打印介质上破坏已打印表面，当供墨压力负压过大时会使得空气被吸入喷孔内使得喷射出的液滴变得杂乱无章。
进一步的，通过对特征参数的计算得到液滴的实时速度，无需再将喷头移至特定位置进行观测，节省了测量时间和空间，简化了测量过程，同时使得用户可以通过实时的速度监测结果来调节相应工艺参数来实现液滴速度的优化控制。
进一步的，通过计算各个特征值并进行比较判断得到各个驱动因素的状态及液滴的速度，当上述任意指标异常时相应的状态指示灯立刻变亮，提醒用户相应故障发生，具有监测过程高效、监测结果明确易懂的特点。
综上所述，本发明提供一种多通道压电式3D打印喷头故障识别及状态监测***及方法，在不使用外加传感器的条件下利用自感应检测方法提取处喷头内部的自感应信号，对自感应信号的特征参数进行计算判断得喷头的喷射状态。能有效识别故障类型及产生原因，提高监测准确性，便于用户采用有效措施；同时无需外部传感器，解决了传感器安装不便问题，通过轮流监测的方式降低了硬件成本；可在喷头工作过程中进行监测，不受喷头位置约束，提高监测灵活性。
【附图说明】
图1为采用自感应方式将压电喷头流道内的压力波信号转化为电信号的压电信号采集电路示意图；
图2为多通道轮流监测电路示意图；
图3为利用压电信号采集电路及数据采集***采集到的自感应信号图；
图4为喷头喷射状态监测流程图；
图5为基于回归模型及算法开发的状态监测示意图；
图6为驱动电压不足导致液滴速度过低的监测效果图；
图7为液体粘度较大导致液滴速度过低的监测效果图；
图8为供墨压力负压过小导致液滴聚集在喷孔表面的监测效果图。
【具体实施方式】
为了使本技术领域的人员更好地理解本发明方案，下面将结合本发明实施例中的附图，对本发明实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例仅仅是本发明一部分的实施例，不是全部的实施例，而并非要限制本发明公开的范围。此外，在以下说明中，省略了对公知结构和技术的描述，以避免不必要的混淆本发明公开的概念。基于本发明中的实施例，本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施例，都应当属于本发明保护的范围。
在附图中示出了根据本发明公开实施例的各种结构示意图。这些图并非是按比例绘制的，其中为了清楚表达的目的，放大了某些细节，并且可能省略了某些细节。图中所示出的各种区域、层的形状及它们之间的相对大小、位置关系仅是示例性的，实际中可能由于制造公差或技术限制而有所偏差，并且本领域技术人员根据实际所需可以另外设计具有不同形状、大小、相对位置的区域/层。
本发明公开的上下文中，当将一层/元件称作位于另一层/元件“上”时，该层/元件可以直接位于该另一层/元件上，或者它们之间可以存在居中层/元件。另外，如果在一种朝向中一层/元件位于另一层/元件“上”，那么当调转朝向时，该层/元件可以位于该另一层/元件“下”。
需要说明的是，本发明的说明书和权利要求书及上述附图中的术语“第一”、“第二”等是用于区别类似的对象，而不必用于描述特定的顺序或先后次序。应该理解这样使用的数据在适当情况下可以互换，以便这里描述的本发明的实施例能够以除了在这里图示或描述的那些以外的顺序实施。此外，术语“包括”和“具有”以及他们的任何变形，意图在于覆盖不排他的包含，例如，包含了一系列步骤或单元的过程、方法、***、产品或设备不必限于清楚地列出的那些步骤或单元，而是可包括没有清楚地列出的或对于这些过程、方法、产品或设备固有的其它步骤或单元。
下面结合附图对本发明做进一步详细描述：
本发明提供了一种多通道压电式3D打印喷头故障识别及状态监测***及方法，利用自感应检测方式将压电喷头流道腔体内的残余振动信号转化为电压信号进行采集分析后得到各种故障发生时对应的特征参数，若特征参数超过阈值则表明发生故障，通过指示灯判断故障类型便于采取处理措施。与传统的基于视频的喷射状态监测方式相比，本发明可以在喷头移动打印过程中实现喷头喷射状态的监测，不受喷头位置限制；同时本发明采用了轮流监测的方式来实现多喷孔的状态监测，大大降低了硬件成本，提高检测效率进而保证打印头工作的稳定性和可靠性。
本发明一种多通道式压电式3D打印喷头故障识别及状态监测***，包括喷头驱动电路、多通道选通电路、压电信号采集电路及监测单元，喷头驱动电路用于提供驱动信号使压电喷头喷射；多通道选通电路用于提供多通道轮流选通信号实现压电喷头多喷孔轮流监测的方案；压电信号采集电路利用自感应检测方式采集压电喷头流道腔体内的残余振动信号；监测单元用于将压电喷头状态检测结果 呈现给用户。
请参阅图1，压电信号采集电路包括喷头电路和等效电路，等效电路包括分压电阻R 2和喷头的等效电容C e，喷头电路包括分压电阻R 1和喷头的静态电容C p，且C p＝C e，R 1＝R 2，输入的驱动电压V in分两路，一路经电阻R 2和电容C e接地，另一路经电阻R 1和电容C p接地，等效电路中电容端电压V 2和喷头电路中电容端电压V 1经压电信号采集电路处理后的输出信号V out与数据采集***连接，用于输出最终结果。
请参阅图2，多通道选通电路包括等效电路、驱动信号发生器、多通道选通开关和多喷孔喷头，压电信号采集电路分两路，一路与多通道选通开关连接，用于提取喷头电路中喷头电容端电压，另一路与等效电路中等效电容C ne的远地端连接，用于提取等效电路中等效电容端电压，；多通道选通开关接收选通信号，并与多喷孔喷头连接。
等效电路包括分压电阻R r和等效电容C ne，第n个喷孔的自感应电压信号V n与等效电路的等效电压信号V r经过压电信号采集电路进行处理，处理后的输出信号V nout与数据采集***连接，用于输出最终结果；驱动信号发生器提供的输入电压V nin分两路，一路经被测量喷孔电路的分压电阻R n及喷孔电路后接地，用于使喷头喷射产生自感应信号V n，另一路经等效电路的分压电阻R r与等效电容C ne后接地，用于输出等效电压信号V r，且R r＝R n。
其中，t h为单通道选通持续时间，t s为相邻通道选通的间隔时间，可通过设置t h调节单通道选通时间。
监测单元包括驱动电压监测、液体粘度监测、供墨压力监测和液滴喷射速度计算模块。
本发明的工作原理为：
1.压电材料具有压电效应，该特性让压电板在喷头***中既可作为驱动器也可作为传感器。
2.当压电板作为传感器时，其内部电流包括充放电效应产生的电流与残余压力波通过压电效应产生的电流两部分。
3.喷头的喷射状态会影响到残余压力波，进而影响到压电板内部的电流，因此采集压电板的电流来分析喷头的喷射状态。
4.利用自感应检测电路的差分特性提取出由压力波所产生的电流并将其转化为电压信号。
5.对自感应电压信号进行采集与分析，建立起喷射故障与特征参数以及液滴速度与特征参数之间的算法模型。
6.基于上述模型，开发状态监测***对喷头喷射状态进行监测，对喷射故障进行识别。
请参阅图4，一种多通道压电式3D打印喷头故障识别及状态监测方法,采用自感应检测方式将压电喷头流道腔体内的残余振动信号转化为电压信号进行采集分析后得到故障发生时对应的特征参数，建立喷射故障与特征参数以及液滴速度与特征参数之间的算法模型，当驱动电压监测、液体粘度监测、供墨压力监测和液滴喷射速度计算模块中各个因素对应的特征参数超过设定阈值时报警灯亮起。
其中，驱动电压监测方案由自感应信号中的尖角幅值作为特征参数进行判断，尖角幅值为采集到的自感应信号的第一个尖角幅值，当该尖角幅值超过设定阈值时即认为驱动电压导致喷射故障；
液体粘度监测方案由自感应信号中的阻尼比作为特征参数进行判断，阻尼比由采集到的自感应信号尾部的残余振动的衰减阻尼比计算所得，计算方法为相邻波峰或波谷的幅值比，当该阻尼比超过设定阈值时即认为液体粘度导致喷射故障；
供墨压力监测方案由自感应信号中的相位作为特征参数进行判断，相位由采集到的自感应信号二阶频率对应的相位计算所得，当该相位超过设定阈值时即认为供墨压力导致喷射故障；
液滴喷射速度计算方案由回归模型计算获得。
液滴喷射速度由各特征参数之间建立的回归模型计算所得，该回归模型基于实验数据拟合所得，并与压电喷头喷射过程的动力学模型基本一致，该实验的因素为驱动电压、液体粘度、供墨压力，因变量为液滴速度。
特征值判断如下：
读取压电信号，依次对时域尖角幅值特征值、残余振动阻尼比特征值和频域相位特征值进行判断；
当时域尖角幅值特征值、残余振动阻尼比特征值和频域相位特征值正常，分别计算液滴速度后结束；
当时域尖角幅值特征值、残余振动阻尼比特征值和频域相位特征值异常，直接结束。
为使本发明实施例的目的、技术方案和优点更加清楚，下面将结合本发明实施例中的附图，对本发明实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例是本发明一部分实施例，而不是全部的实施例。通常在此处附图中的描述和所示的本发明实施例的组件可以通过各种不同的配置来布置和设计。因此，以下对在附图中提供的本发明的实施例的详细描述并非旨在限制要求保护的 本发明的范围，而是仅仅表示本发明的选定实施例。基于本发明中的实施例，本领域普通技术人员在没有作出创造性劳动前提下所获得的所有其他实施例，都属于本发明保护的范围。
在一个实例中，通过喷头驱动电路对某一选定喷孔进行喷射，采用压电信号采集电路和数据采集***对压电喷头流道腔体内的压力波信号进行提取采集，当喷头驱动电压过小导致液滴喷射速度低于正常值或者驱动电压过大使得主液滴周围产生卫星液滴时，此时监测软件界面上电压指示灯亮，表明是由电压导致的液滴喷射故障。
在一个实例中，通过喷头驱动电路对某一选定喷孔进行喷射，采用压电信号采集电路和数据采集***对压电喷头流道腔体内的压力波信号进行提取采集，当被喷射液体粘度过大导致液滴喷射速度低于正常值或者液滴粘度很小使得主液滴尾部的液柱较长时，此时监测软件界面上粘度指示灯亮，表明是由粘度导致的液滴喷射故障。
在一个实例中，通过喷头驱动电路对某一选定喷孔进行喷射，采用压电信号采集电路和数据采集***对压电喷头流道腔体内的压力波信号进行提取采集，当供墨压力负压过小时导致喷孔有液滴聚集无法喷射或者当供墨压力负压过大导致喷孔内吸入气泡无法喷射时，监测软件界面上压力指示灯均会亮，表明是由压力导致的液滴喷射故障。
在一个实例中，通过喷头驱动电路对某一选定喷孔进行喷射，采用压电信号采集电路和数据采集***对压电喷头流道腔体内的压力波信号进行提取采集，当喷射条件均处在正常范围内时，此时监测软件界面上各因素的指示灯均正常，表明此时处于正常喷射状态，与此同时可以通过回归模型计算出的速度值来反映液 滴的喷射速度，该速度计算值与采用观墨设备测量的实际值基本一致，表明该状态监测软件能有效计算出液滴速度。
在一个实例中，通过喷头驱动电路和多通道选通电路对一个具有16个喷孔的喷头进行轮流喷射，采用压电信号采集电路对流道腔体内的残余振动信号进行采集，并通过监测软件计算出每个喷孔的液滴喷射速度，可以实现多喷孔的液滴速度监测。
请参阅图5，为基于回归模型及算法开发的状态监测软件界面，包括串口配制、采样设置、波形显示、监测状态结果显示等模块，该界面能直接有效地显示出引起喷头喷射故障的原因及正常喷射时液滴的速度；
图6～8中左侧为监测界面，右侧黑点为通过观墨设备采集到的液滴实时图像，可测量液滴速度，用以进行对比验证本发明的监测效果，所用观墨设备为杭州米杰公司的MiWatcher设备，液滴位置越靠上表明液滴速度越低，当液滴速度低于参考值时认为发生喷射故障，本发明中参考速度设为5m/s。
请参阅图6，为驱动电压不足导致液滴速度过低的监测效果，通过人为降低驱动电压，使得液滴速度变为4.49m/s，即为故障状态，此时驱动电压对应的状态指示灯变量，表示由驱动电压引起的故障；
请参阅图7，为液体粘度较大导致液滴速度过低的监测效果，通过更换高粘度液滴进行喷射，观墨设备测量的液滴速度为2.88m/s，即为故障状态，此时液体粘度对应的指示灯变亮，表示由喷射液体粘度引起的故障；
请参阅图8，为供墨压力正压过大导致液滴聚集在喷孔表面的监测效果，通过人为升高供墨压力使得液滴聚集在喷孔表面，即为故障状态，此时供墨压力对应的指示灯变量，表示由供墨压力引起的故障。
由图6～8的监测效果表明，当实际喷射故障发生时，本发明能立即提醒用户喷头发生故障并能有效识别故障类型，避免盲目处理。
以上内容仅为说明本发明的技术思想，不能以此限定本发明的保护范围，凡是按照本发明提出的技术思想，在技术方案基础上所做的任何改动，均落入本发明权利要求书的保护范围之内。

Claims (10)

  1. 多通道压电式3D打印喷头故障识别及状态监测***，其特征在于，包括喷头驱动电路、多通道选通电路、压电信号采集电路及监测单元，喷头驱动电路用于提供驱动信号使压电喷头喷射；多通道选通电路用于提供多通道轮流选通信号实现压电喷头多喷孔轮流监测；压电信号采集电路利用自感应检测方式采集压电喷头流道腔体内的残余振动信号；监测单元包括驱动电压监测、液体粘度监测、供墨压力监测和液滴喷射速度计算模块，用于监测压电喷头工作状态。
  2. 根据权利要求1所述的多通道压电式3D打印喷头故障识别及状态监测***，其特征在于，压电信号采集电路包括喷头电路和等效电路，等效电路包括分压电阻R 2和喷头的等效电容C e，喷头电路包括分压电阻R 1和喷头的静态电容C p，且C p＝C e，R 1＝R 2，输入的驱动电压V in分两路，一路经电阻R 2和电容C e接地，另一路经电阻R 1和电容C p接地，等效电路中电容端电压V 2和喷头电路中电容端电压V 1经压电信号采集电路处理后的输出信号V out与数据采集***连接，用于输出最终结果。
  3. 根据权利要求1或2所述的多通道压电式3D打印喷头故障识别及状态监测***，其特征在于，多通道选通电路包括等效电路、驱动信号发生器、多通道选通开关和多喷孔喷头，压电信号采集电路分两路，一路与多通道选通开关连接，用于提取喷头电路中喷头电容端电压，另一路与等效电路中等效电容C ne的远地端连接，用于提取等效电路中等效电容端电压；多通道选通开关接收选通信号，并与多喷孔喷头连接。
  4. 根据权利要求3所述的多通道压电式3D打印喷头故障识别及状态监测***，其特征在于，等效电路包括分压电阻R r和等效电容C ne，第n个喷孔的自感应电压信号V n与等效电路的等效电压信号V r经过压电信号采集电路进行处理， 处理后的输出信号V nout与数据采集***连接，用于输出最终结果；驱动信号发生器提供的输入电压V nin分两路，一路经被测量喷孔电路的分压电阻R n及喷孔电路后接地，用于使喷头喷射产生自感应信号V n，另一路经等效电路的分压电阻R r与等效电容C ne后接地，用于输出等效电压信号V r，且R r＝R n。
  5. 一种多通道压电式3D打印喷头故障识别及状态监测方法，其特征在于，利用权利要求1至4中任一项所述的多通道压电式3D打印喷头故障识别及状态监测***，采用自感应检测方式将压电喷头流道腔体内的残余振动信号转化为电压信号进行采集分析后得到故障发生时对应的特征参数，建立喷射故障与特征参数以及液滴速度与特征参数之间的算法模型，当驱动电压监测、液体粘度监测、供墨压力监测和液滴喷射速度计算模块中各个因素对应的特征参数超过阈值则表明发生故障。
  6. 根据权利要求5所述的多通道式压电式3D打印喷头故障识别及状态监测***，其特征在于，驱动电压监测由自感应信号中的尖角幅值作为特征参数进行判断，尖角幅值为采集到的自感应信号的第一个尖角幅值，通过喷头驱动电路对某一选定喷孔进行喷射，采用压电信号采集电路和数据采集***对压电喷头流道腔体内的压力波信号进行提取采集，当喷头驱动电压过小导致液滴喷射速度低于正常值或驱动电压过大使得主液滴周围产生卫星液滴时，驱动电压对应的指示灯亮起，表明是由电压导致的液滴喷射故障。
  7. 根据权利要求5所述的多通道式压电式3D打印喷头故障识别及状态监测***，其特征在于，液体粘度监测由自感应信号中的阻尼比作为特征参数进行判断，阻尼比由采集到的自感应信号尾部的残余振动的衰减阻尼比计算所得，通过喷头驱动电路对某一选定喷孔进行喷射，采用压电信号采集电路和数据采集*** 对压电喷头流道腔体内的压力波信号进行提取采集，当被喷射液体粘度过大导致液滴喷射速度低于正常值或液滴粘度很小使得主液滴尾部的液柱较长时，液体粘度对应的指示灯亮起，表明是由粘度导致的液滴喷射故障。
  8. 根据权利要求5所述的多通道式压电式3D打印喷头故障识别及状态监测***，其特征在于，供墨压力监测由自感应信号中的相位作为特征参数进行判断，相位由采集到的自感应信号相位计算所得，通过喷头驱动电路对某一选定喷孔进行喷射，采用压电信号采集电路和数据采集***对压电喷头流道腔体内的压力波信号进行提取采集，当供墨压力负压过小时导致喷孔有液滴聚集无法喷射或当供墨压力负压过大导致喷孔内吸入气泡无法喷射时，供墨压力对应的指示灯亮起，表明是由压力导致的液滴喷射故障。
  9. 根据权利要求5所述的多通道式压电式3D打印喷头故障识别及状态监测***，其特征在于，液滴喷射速度计算方案由回归模型计算获得，通过喷头驱动电路对某一选定喷孔进行喷射，采用压电信号采集电路和数据采集***对压电喷头流道腔体内的压力波信号进行提取采集，当喷射条件在正常范围内时，表明处于正常喷射状态，通过回归模型计算出的速度值反映液滴的喷射速度。
  10. 根据权利要求5至9中任一项所述的多通道式压电式3D打印喷头故障识别及状态监测***，其特征在于，特征值判断步骤如下：
    S1.读取压电信号，依次对时域尖角幅值特征值、残余振动阻尼比特征值和频域相位特征值进行判断；
    S2、当时域尖角幅值特征值、残余振动阻尼比特征值和频域相位特征值均正常时，计算液滴速度后结束；
    S3、当时域尖角幅值特征值、残余振动阻尼比特征值和频域相位特征值中的 任意一个产生异常时，直接结束。
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