CN105181375A - 3D printer fault detection method - Google Patents
3D printer fault detection method Download PDFInfo
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- CN105181375A CN105181375A CN201510711240.7A CN201510711240A CN105181375A CN 105181375 A CN105181375 A CN 105181375A CN 201510711240 A CN201510711240 A CN 201510711240A CN 105181375 A CN105181375 A CN 105181375A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
- G01M99/00—Subject matter not provided for in other groups of this subclass
- G01M99/005—Testing of complete machines, e.g. washing-machines or mobile phones
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
- G01M99/00—Subject matter not provided for in other groups of this subclass
- G01M99/002—Thermal testing
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Abstract
The invention provides a 3D printer fault detection method, which particularly aims at a temperature aspect, solving the problem in the prior art that 3D printer fault detection is lack of repeated effect. With the adoption of the method, the complicated application requirements can be met by the sensitivity and control flexibility of a 3D printer under situations that temperature difference is relatively small and control requirements are precise when the 3D printer is used for producing fused materials such as the situations of medical device products and complex type workpieces.
Description
Technical field
The present invention relates to 3D printer fault detection technique field, more specifically, relate to a kind of 3D printer temperature fault detection method.
Background technology
Along with the continuous progress of 3D printing technique, people are proposed higher requirement to the function of 3D printer, performance and reliability.3D printer, as a kind of emerging process equipment, has more and more wide application prospect and market potential.3D printer is many based on FDM principle on the market at present, namely Fused Deposition Modeling principle.The starting material of this kind of 3D printer are generally thermoplastics, as wax, ABS, nylon etc.Detection for temperature is most important.
In prior art, Chinese patent application CN201410489881.8 discloses a kind of 3D printer duty on-Line Monitor Device.Comprise digital sampling and processing and power module, described digital sampling and processing comprises microprocessor, camera, humidity temperature pickup module, Velocity-acceleration sensor, communication module, sound and light alarm, open circuit protection, liquid crystal display and keyboard input module.The picture of shower nozzle and workpiece during the work of camera Real-time Collection 3D printer, Temperature Humidity Sensor module gathers shower nozzle, baseplate temp and environment temperature and humidity information respectively, the Velocity-acceleration of base plate measured in real time by Velocity-acceleration sensor, and processor will be sent to host computer after above information processing and liquid crystal display shows in real time.When humiture parameter or Velocity-acceleration parameter exceed setting range, device cuts off 3D printer power supply by breaker protector, realizes anxious stopping and protects.
Because the use of 3D printer exists intermittent process, namely need after may using a period of time due to a variety of causes a period of time out of service, and then startup optimization, therefore, the remaining vestiges of cooling after the existence of the parts such as heater block, transfer unit is once heated may be caused when again running.These vestiges skewness and become more serious along with the shortening in serviceable life.Existing 3D printer just detects limited temperature information in heating process, such as heating element temperature etc.But, effective detection is but lacked for above-mentioned vestiges situation, causes the inaccurate problem of temperature detection in 3D printer process that reuses.This 3D printer time and again effect is especially unfavorable for the occasion that materials processing precision requirement is higher.
Summary of the invention
In order to overcome the problem fault detect of 3D printer being lacked time and again to effect consideration existed in prior art, the invention provides a kind of especially for the 3D printer fault detection method of temperature aspect.The method comprises:
(1) before 3D printer starts charging and heating, detect the temperature in space, place, 3D printer heater block place, be designated as first environment temperature;
(2) open 3D printer, detect the inlet amount of charging aperture, record the ratio of inlet amount relative to the time of this material, be designated as this ratio;
(3) when this ratio described is greater than predetermined threshold, detect the temperature of 3D printer heater block, remember that this temperature is the first temperature of charge;
(4) detect the temperature of charge at 3D printer spray material port place, remember that this temperature is the second temperature of charge;
(5) record described first temperature of charge and exceed the first transformation period that first environment temperature predetermined threshold spends;
(6) when the first temperature of charge is within a certain period of time all higher than the first predetermined temperature, record from unlatching 3D printer to now the spent time, obtained for the first stabilization time according to this time and above-mentioned first transformation period;
(7) when the second temperature of charge is within a certain period of time all higher than the second predetermined temperature, record from unlatching 3D printer to now the spent time, be designated as the second stabilization time;
(8) store this above-mentioned first transformation period using 3D printer, the first stabilization time and the second stabilization time, and calculate vestiges accumulation factor according to above-mentioned first transformation period, the first stabilization time and the second stabilization time;
(9) according to this use this ratio above-mentioned of 3D printer, the first transformation period, the first stabilization time, the second stabilization time, vestiges accumulation factor and storage before use the average vestiges coefficient of 3D printer to judge whether 3D printer is in malfunction.
Further, described step (2) comprises further: after opening 3D printer, the service time of cumulative record 3D printer, is designated as and accumulates service time.
Further, obtain according to this time and above-mentioned first transformation period in described step (6) and comprise for the first stabilization time: utilize the difference from opening 3D printer and to deduct to now the spent time the first transformation period, obtained for the first stabilization time.
Further, calculating vestiges accumulation factor in described step (8) is:
Vestiges accumulation factor=((first stabilization time-the first transformation period)/(second stabilization time-the first transformation period)) * 100%.
Further, described step (9) comprising:
(9.1) the stored ratio of inlet amount relative to the time using 3D printer is before searched, with the one or many ratio before determining to be less than predetermined threshold value with the difference of this ratio, then to this one or many ratio calculation mean value determined, history average of relatives value is designated as;
(9.2) the stored vestiges accumulation factor using 3D printer is before searched, with the one or many vestiges accumulation factor before determining to be less than predetermined threshold value with the difference of this vestiges accumulation factor, then to this one or many vestiges accumulation factor calculating mean value determined, history vestiges accumulation factor mean value is designated as;
(9.3) judge whether 3D printer is in malfunction according to this ratio, history average of relatives value, the first transformation period, the first stabilization time, the second stabilization time, vestiges accumulation factor and history vestiges accumulation factor mean value.
Further, described step (9.3) comprises calculating defective proportion coefficient according to the following formula:
Defective proportion coefficient=((this ratio/history average of relatives value)/(vestiges accumulation factor/history vestiges accumulation factor mean value)) * (first stabilization time * first transformation period/the second * stabilization time second stabilization time); When this defective proportion coefficient is less than predetermined threshold value, think that 3D printer does not occur that above-mentioned vestiges fault or vestiges not yet affect the normal of 3D printer; Otherwise point out the vestiges of this 3D printer to affect its heating accuracy.
The invention has the beneficial effects as follows: make using 3D printer the occasion that melting material temperature difference is less, control overflow is accurate, the such as occasion such as medical device product, compound workpiece, can guarantee that the sensitivity of 3D printer and control flexibility ratio meet complicated applications demand.
Accompanying drawing explanation
Fig. 1 shows the process flow diagram of fault detection method of the present invention.
Embodiment
As shown in Figure 1,3D printer fault detection method of the present invention comprises the steps:
(1) before 3D printer starts charging and heating, detect the temperature in space, place, 3D printer heater block place, be designated as first environment temperature;
(2) open 3D printer, detect the inlet amount of charging aperture, record the ratio of inlet amount relative to the time of this material, be designated as this ratio;
(3) when this ratio described is greater than predetermined threshold, detect the temperature of 3D printer heater block, remember that this temperature is the first temperature of charge; Here predetermined threshold is generally determine according to the model of concrete 3D printer and selected material.Such as, for AURORA3D printer, adopt the blue consumptive material of MakerBotPLA, threshold value herein can be set to 4.3mm/s.
(4) detect the temperature of charge at 3D printer spray material port place, remember that this temperature is the second temperature of charge;
(5) record described first temperature of charge and exceed the first transformation period that first environment temperature predetermined threshold spends; Predetermined threshold herein can be 25 DEG C ± 2 DEG C.
(6) when the first temperature of charge is within a certain period of time all higher than the first predetermined temperature, record from unlatching 3D printer to now the spent time, obtained for the first stabilization time according to this time and above-mentioned first transformation period; Corresponding to the blue consumptive material material of above-mentioned MakerBotPLA, the first predetermined temperature is herein such as 130 DEG C ± 5 DEG C.
(7) when the second temperature of charge is within a certain period of time all higher than the second predetermined temperature, record from unlatching 3D printer to now the spent time, be designated as the second stabilization time; Corresponding to the blue consumptive material material of above-mentioned MakerBotPLA, the second predetermined temperature is herein such as 150 DEG C ± 5 DEG C.
(8) store this above-mentioned first transformation period using 3D printer, the first stabilization time and the second stabilization time, and calculate vestiges accumulation factor according to above-mentioned first transformation period, the first stabilization time and the second stabilization time;
(9) according to this use this ratio above-mentioned of 3D printer, the first transformation period, the first stabilization time, the second stabilization time, vestiges accumulation factor and storage before use the average vestiges coefficient of 3D printer to judge whether 3D printer is in malfunction.
Principle of the present invention is: temperature when being in steady-working state by gathering multiple position and the time experienced, and cut and rise to predetermined threshold (the regulation melt temperature of such as material) this setup time (because it has uncertainty with variation of ambient temperature from environment temperature, therefore need to remove this factor), again by the vestiges accumulation factor with approximate charging rate in historical record, the inlet amount of material is multiplied relative to the ratio etc. of time, when finally obtaining characterizing 3D this task of printer, material melts the coefficient of the fault causing the temperature control precision that 3D printer melts material to be deteriorated, and carry out breakdown judge as threshold value based on experience value.
Preferably, described step (2) comprises further: after opening 3D printer, the service time of cumulative record 3D printer, is designated as and accumulates service time.
Preferably, obtain according to this time and above-mentioned first transformation period in described step (6) and comprise for the first stabilization time: utilize the difference from opening 3D printer and to deduct to now the spent time the first transformation period, obtained for the first stabilization time.
Preferably, calculating vestiges accumulation factor in described step (8) is:
Vestiges accumulation factor=((first stabilization time-the first transformation period)/(second stabilization time-the first transformation period)) * 100%.
Preferably, described step (9) comprising:
(9.1) the stored ratio of inlet amount relative to the time using 3D printer is before searched, with the one or many ratio before determining to be less than predetermined threshold value with the difference of this ratio, then to this one or many ratio calculation mean value determined, history average of relatives value is designated as;
(9.2) the stored vestiges accumulation factor using 3D printer is before searched, with the one or many vestiges accumulation factor before determining to be less than predetermined threshold value with the difference of this vestiges accumulation factor, then to this one or many vestiges accumulation factor calculating mean value determined, history vestiges accumulation factor mean value is designated as;
(9.3) judge whether 3D printer is in malfunction according to this ratio, history average of relatives value, the first transformation period, the first stabilization time, the second stabilization time, vestiges accumulation factor and history vestiges accumulation factor mean value.
Preferably, described step (9.3) comprises calculating defective proportion coefficient according to the following formula:
Defective proportion coefficient=((this ratio/history average of relatives value)/(vestiges accumulation factor/history vestiges accumulation factor mean value)) * (first stabilization time * first transformation period/the second * stabilization time second stabilization time); When this defective proportion coefficient is less than predetermined threshold value, think that 3D printer does not occur that above-mentioned vestiges fault or vestiges not yet affect the normal of 3D printer; Otherwise point out the vestiges of this 3D printer to affect its heating accuracy.In this comparison procedure, this predetermined threshold value can choose the value between 0.2 ~ 0.5.
The mode illustrated with word and accompanying drawing above illustrates step and the flow process of some embodiments of the present invention, not exhaustive or be limited to concrete form described above.It should be pointed out that for those skilled in the art, under the premise without departing from the principles of the invention, can also make some improvements and modifications, these improvements and modifications also should be considered as protection scope of the present invention.
Claims (6)
1. a 3D printer fault detection method, comprising:
(1) before 3D printer starts charging and heating, detect the temperature in space, place, 3D printer heater block place, be designated as first environment temperature;
(2) open 3D printer, detect the inlet amount of charging aperture, record the ratio of inlet amount relative to the time of this material, be designated as this ratio;
(3) when this ratio described is greater than predetermined threshold, detect the temperature of 3D printer heater block, remember that this temperature is the first temperature of charge;
(4) detect the temperature of charge at 3D printer spray material port place, remember that this temperature is the second temperature of charge;
(5) record described first temperature of charge and exceed the first transformation period that first environment temperature predetermined threshold spends;
(6) when the first temperature of charge is within a certain period of time all higher than the first predetermined temperature, record from unlatching 3D printer to now the spent time, obtained for the first stabilization time according to this time and above-mentioned first transformation period;
(7) when the second temperature of charge is within a certain period of time all higher than the second predetermined temperature, record from unlatching 3D printer to now the spent time, be designated as the second stabilization time;
(8) store this above-mentioned first transformation period using 3D printer, the first stabilization time and the second stabilization time, and calculate vestiges accumulation factor according to above-mentioned first transformation period, the first stabilization time and the second stabilization time;
(9) according to this use this ratio above-mentioned of 3D printer, the first transformation period, the first stabilization time, the second stabilization time, vestiges accumulation factor and storage before use the average vestiges coefficient of 3D printer to judge whether 3D printer is in malfunction.
2. method according to claim 1, is characterized in that, described step (2) comprises further: after opening 3D printer, the service time of cumulative record 3D printer, is designated as and accumulates service time.
3. method according to claim 1, it is characterized in that, obtain according to this time and above-mentioned first transformation period in described step (6) and comprise for the first stabilization time: utilize the difference from opening 3D printer and to deduct to now the spent time the first transformation period, obtained for the first stabilization time.
4. method according to claim 1, is characterized in that, calculates vestiges accumulation factor to be in described step (8):
Vestiges accumulation factor=((first stabilization time-the first transformation period)/(second stabilization time-the first transformation period)) * 100%.
5. method according to claim 1, is characterized in that, described step (9) comprising:
(9.1) the stored ratio of inlet amount relative to the time using 3D printer is before searched, with the one or many ratio before determining to be less than predetermined threshold value with the difference of this ratio, then to this one or many ratio calculation mean value determined, history average of relatives value is designated as;
(9.2) the stored vestiges accumulation factor using 3D printer is before searched, with the one or many vestiges accumulation factor before determining to be less than predetermined threshold value with the difference of this vestiges accumulation factor, then to this one or many vestiges accumulation factor calculating mean value determined, history vestiges accumulation factor mean value is designated as;
(9.3) judge whether 3D printer is in malfunction according to this ratio, history average of relatives value, the first transformation period, the first stabilization time, the second stabilization time, vestiges accumulation factor and history vestiges accumulation factor mean value.
6. method according to claim 5, is characterized in that, described step (9.3) comprises calculating defective proportion coefficient according to the following formula:
Defective proportion coefficient=((this ratio/history average of relatives value)/(vestiges accumulation factor/history vestiges accumulation factor mean value)) * (first stabilization time * first transformation period/the second * stabilization time second stabilization time); When this defective proportion coefficient is less than predetermined threshold value, think that 3D printer does not occur that above-mentioned vestiges fault or vestiges not yet affect the normal of 3D printer; Otherwise point out the vestiges of this 3D printer to affect its heating accuracy.
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| CN201710946570.3A CN107655710B (en) | 2015-10-28 | 2015-10-28 | 3D printer fault detection method |
| CN201510711240.7A CN105181375B (en) | 2015-10-28 | 2015-10-28 | 3D printer fault detection method |
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN106382953A (en) * | 2016-09-06 | 2017-02-08 | 芜湖纯元光电设备技术有限公司 | 3D printer fault determination and storage method based on temperature detection |
| CN107053657A (en) * | 2017-04-06 | 2017-08-18 | 江苏海事职业技术学院 | A kind of 3D printer fault detection method based on temperature detection |
| CN107081899A (en) * | 2017-05-10 | 2017-08-22 | 山东大学 | A kind of antenna production method based on 3D printing |
| CN109049676A (en) * | 2018-08-10 | 2018-12-21 | 陈劲松 | A kind of 3D printer pallet and 3D printer |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110849646A (en) * | 2019-10-17 | 2020-02-28 | 中国航空工业集团公司洛阳电光设备研究所 | Method for testing temperature stabilization time of product |
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| CN106382953A (en) * | 2016-09-06 | 2017-02-08 | 芜湖纯元光电设备技术有限公司 | 3D printer fault determination and storage method based on temperature detection |
| CN107053657A (en) * | 2017-04-06 | 2017-08-18 | 江苏海事职业技术学院 | A kind of 3D printer fault detection method based on temperature detection |
| CN107081899A (en) * | 2017-05-10 | 2017-08-22 | 山东大学 | A kind of antenna production method based on 3D printing |
| CN109049676A (en) * | 2018-08-10 | 2018-12-21 | 陈劲松 | A kind of 3D printer pallet and 3D printer |
Also Published As
| Publication number | Publication date |
|---|---|
| CN107655710A (en) | 2018-02-02 |
| CN107655710B (en) | 2019-08-13 |
| CN105181375B (en) | 2017-11-21 |
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