- Open Access
Actualities and Development of Heavy-Duty CNC Machine Tool Thermal Error Monitoring Technology
© The Author(s) 2017
- Received: 6 April 2016
- Accepted: 6 July 2017
- Published: 25 July 2017
Thermal error monitoring technology is the key technological support to solve the thermal error problem of heavy-duty CNC (computer numerical control) machine tools. Currently, there are many review literatures introducing the thermal error research of CNC machine tools, but those mainly focus on the thermal issues in small and medium-sized CNC machine tools and seldom introduce thermal error monitoring technologies. This paper gives an overview of the research on the thermal error of CNC machine tools and emphasizes the study of thermal error of the heavy-duty CNC machine tool in three areas. These areas are the causes of thermal error of heavy-duty CNC machine tool and the issues with the temperature monitoring technology and thermal deformation monitoring technology. A new optical measurement technology called the “fiber Bragg grating (FBG) distributed sensing technology” for heavy-duty CNC machine tools is introduced in detail. This technology forms an intelligent sensing and monitoring system for heavy-duty CNC machine tools. This paper fills in the blank of this kind of review articles to guide the development of this industry field and opens up new areas of research on the heavy-duty CNC machine tool thermal error.
- Heavy-duty CNC machine tool
- Thermal error
- Temperature field
- Deformation field
- Fiber Bragg grating
The history of the study of the machine tool thermal error is close to a century long. There is still no solution to the thermal error problem with modern high precision CNC machine tools. Most research about the machine tool thermal error has focused on establishing the relationship between the temperature field and thermal error of machine tools, but no solutions have presented themselves well in industry application. Since there have been no new technological breakthroughs in the experimental studies on the thermal error, traditional electrical testing and laser measurement technology are commonly used. The research objects in thermal error testing are usually small and medium-sized CNC machine tools. There is relatively less research on heavy-duty CNC machine tools.
Geometric errors produced by machine parts’ manufacturing and assembly;
Thermal-induced deformation errors caused by internal and external heat sources;
Force-induced deformation errors caused by the cutting force, clamping force, machine tool’s own gravity, etc.;
Control errors caused by issues such as the response lag, positioning detection error of the servo system, CNC interpolation algorithm, etc.;
Tool wear and the high frequency flutter of the machine tool.
The proportion of the thermal deformation error is often the largest for high precision CNC machine tools. In precision manufacturing, the thermal deformation error accounts for about 40% – 70% of the total machining errors . In 1933, the influence of heat on precision part processing was noticed for the first time . A number of qualitative analysis and contrast tests were carried out between the 1930s and the 1960s. Until the 1970s, researchers used the finite element method (FEM) for machine tool thermal deformation calculations and the optimization of the design of machine tools. The CNC thermal error compensation technology appeared in the late 1970s. After the 1990s, thermal error compensation technology rapidly developed, and many research institutions conducted in-depth studies on the thermal error compensation technology of CNC machine tools based on temperature measurements [4–14].
Over the past few decades, the International Organization for Standardization (ISO) promulgated a series of standards: ISO 230-3 (thermal deformation of the machine tool) , ISO 10791-10 (thermal deformation of the machining center) , and ISO 13041-8 (thermal distortion of the turning center) . These standards provide systemic analysis methods for machine tool thermal behavior.
Larger and heavier moving parts, like the spindle box, moving beam, and moving workbench;
Larger and more complex support structures, such as the machine tool base, column, and beam;
More decentralized internal heat sources in 3-D (3-dimensional) space;
Greater susceptibility to environmental temperature shifts.
As the temperature varies over time and the moving parts are heavy, the thermal and mechanical errors exist a strong coupling effect, making the thermal deformation mechanism more complicated and the optimization of the structural design more difficult. As heavy-duty CNC machine tools are more susceptible to environmental temperature shifts (due to the large volume, small changes of environmental temperature can cause noteworthy accumulations of thermal expansion of the machine tool structure in 3-D space), the robustness of the thermal error prediction model of heavy-duty CNC machine tools is more difficult to control.
In terms of temperature field monitoring, as heavy-duty CNC machine tools have a large volume and dispersive heat sources, more temperature measuring points are needed in order to establish an accurate temperature field distribution. Additionally, the installation positions of temperature sensors are more difficult to determine, and the optimization of the temperature measuring points is more complex;
In terms of thermal deformation monitoring, there are lots of similarity in position error monitoring of the cutting tool tip between the heavy-duty machine tool and other machine tools. However, for thermal deformation field monitoring of the large structural parts, the Heavy-duty CNC machine tools face greater challenges. The existing machine tool deformation detection techniques are mostly based on the displacement detection instruments, which only detect one point or a few points’ displacement of the machine tool structure. These methods estimate the deformation by the interpolation method. As the structural parts of the heavy-duty CNC machine tool are larger, more conventional displacement sensors or displacement measurement instruments with wide measurement range in the space are needed to reconstruct the whole thermal deformation of the structures. Additionally, as the moving parts of the heavy-duty CNC machine tool are rather heavier than the small and medium-sized CNC machine tools, when the machine tool works, the sedimentation deformation and vibration of the reinforced concrete foundation is more serious and intractable, which reduces the displacement measurement accuracy directly;
The processing environment of heavy-duty CNC machine tool is generally worse than the small and medium-sized CNC machine tools. Traditional electric sensors can be easily influenced by the work environment. Humidity, dust, oil pollution, and electromagnetic interference all reduce the sensors’ performance stability and reliability. The long-term thermal error monitoring of the heavy-duty CNC machine tools requires better environmental adaptability and higher reliability to the related sensors.
In order to solve the thermal issues of heavy-duty CNC machine tools, we need to analyze the causes of thermal error of machine tool and then carry out in-depth study on the thermal deformation mechanism based on the existing theory and thermal deformation detection technology. In addition, we need to conclude the existing monitoring technologies and provides new technical support for thermal error research on heavy-duty CNC machine tools.
Currently, there are many review literatures on the thermal error of CNC machine tools [2, 18–26], but these papers mainly focus on the thermal issues in small and medium-sized CNC machine tools and seldom introduce thermal error monitoring technologies. This paper focuses on the study of thermal error of the heavy-duty CNC machine tool and emphasizes on its thermal error monitoring technology. First, the causes of thermal error of the heavy-duty CNC machine tool are discussed in Section 2, where the heat generation in the spindle and feed system and the environmental temperature influence are introduced. Then, the temperature monitoring technology and thermal deformation monitoring technology are reviewed in detail in Sections 3 and 4, respectively. Finally, in Section 5, the application of the new optical measurement technology, the “fiber Bragg grating distributed sensing technology” for heavy-duty CNC machine tools is discussed. This technology is an intelligent sensing and monitoring system for heavy-duty CNC machine tools and opens up new areas of research on the heavy-duty CNC machine tool thermal error.
2.1 Classification of the Heat Sources
Internal heat sources
External heat sources
Environmental temperature variation; Thermal radiation from the sun and other light sources.
For the internal heat sources, the heat generated from the spindle and ball screws has a significant influence on the heavy-duty CNC machine tools and appears frequently in the literatures. The heating mechanism, thermal distribution, and thermal-induced deformation are often researched by theoretical and experimental methods. For the external heat sources, the dynamic change regularity of the environmental temperature and its individual influence and combined effects with internal heat sources on thermal error of heavy-duty CNC machine tools are studied.
2.2 Heat Generated in the Spindle
2.2.1 Thermal Model of the Supporting Bearing
The above models calculate the thermogenesis value of the rolling bearing as a whole, and they do not involve the the surface friction power loss calculation of the inner concrete components of the bearing. Rumbarger, et al. , used the established fluid traction torque model to calculate the friction power loss of the bearing roller, cage, and inner and outer ring raceway respectively. But their model ignored the heating mechanism differences between the local heat sources. Chen, et al. , calculated the total thermogenesis of the bearing from the local heat sources with different heating mechanisms. Moorthy and Raja  calculated the thermogenesis value of the local heat sources, they also took into consideration the change in the diametral clearance after the assembly and during operation that was attributed to the thermal expansion of the bearing parts, which influenced the gyroscopic and spinning moments contributing to the heat generation. Hannon  detailed the existing thermal models for the rolling-element bearing.
2.2.2 Thermal Distribution in the Spindle
As the real structure of a spindle box is complicated, the finite difference method (FDM) and FEM are often preferred to obtain accurate results. Jedrzejewski, et al. , set up a thermal analysis model of a high precision CNC machining center spindle box using a combination of the FEM and the FDM. Refs. [41, 42] created an axially symmetric model for a single shaft system with one pair of bearings using the FEM to estimate the temperature distribution of the whole spindle system.
2.3 Heat Generated in the Feed Screw Nuts
Mayr, et al. , established the equivalent thermal network model of the ball screw with an analytical method. Xu, et al. [44, 47], discovered that, in the case of a large stroke, the heat produced by the moving nut was dispersed on a larger scale than in other cases, so the screw cooling method has better deformation performance than the nut cooling method. Conversely, in the case of a small stroke, the thermal deformation performance of the nut cooling method is better than that of the screw cooling method. Some researchers [4, 48, 49] developed the FEM model for the screw, in which the strength of the heat source measured by the temperature sensors was applied to the FEM model to calculate the thermal errors of the feed drive system. Jin, et al. [50–52], presented an analytical method to calculate the heat generation rate of a ball bearing in the ball screw/nut system with respect to the rotational speed and load applied to the feed system.
2.4 Environmental Temperature Effects
Zhang, et al. , established the thermal error transfer function of each object of the machine tool based on the heat transfer mechanism. Then, based on the assembly dimension chain principle, the thermal error transfer function of the whole machine tool was obtained. As the thermal error transfer function can be deduced using Laplace transform, the thermal error characteristic of the machine tool can be studied with both time domain and frequency domain methods. Taking the environmental temperature fluctuations as input, based on the thermal error transfer function, the environmental temperature induced thermal error can be obtained.
2.5 Thermal Analysis of the Global Machine Tool
The transient 3-D temperature distribution at discrete points of time during the simulated period was calculated using the FDM. Those were then used as temperature field for the FEM to calculate the thermally induced deformations.
The formation process of thermal errors in heavy-duty CNC machine tools occurs in the following steps: heat sources→temperature field→thermal deformation field→thermal error. It is obvious that the relationship between the thermal deformation field and thermal error is more relevant than the relationship between the temperature field and thermal error. However, it is quite difficult to measure the micro-thermal-deformation of the whole machine structure directly and the surface temperature of the machine tool is easier to obtain inversely. Existing thermal error prediction models are mostly based on the temperature measurement from the surface of the machine tool, establishing the relationship between the thermal drift of the cutting tool tip and the temperature at critical measuring point. Therefore, the temperature monitoring of the machine tool is a key technology in the thermal error research of CNC machine tools. It can be divided into the contact-type temperature measurements and non-contact temperature measurements, according to the installation form of the temperature sensor.
3.1 Contact-Type Temperature Measurement of Heavy-Duty CNC Machine Tools
The contact-type surface temperature measurement sensors used in the temperature monitoring of CNC machine tools are mainly thermocouples and platinum resistance temperature detector (RTD). Their installation can be divided into the paste-type, pad-type, and screw-type. Thermocouples and platinum resistance temperature detectors are mostly used for discrete surface temperature measurement. Heavy-duty CNC machine tools have a large volume and decentralized internal heat sources.
Poor environmental adaptability
Weak ability to resist electromagnetic interference
Wide variety of signal transmission wires
The principle of electrical temperature sensors is that of an electrically closed circuit. A single electrical temperature sensor has two conductor wires, and a plurality of electrical sensors cannot be connected in a series connection. If there are N electrical sensors, there are 2N wires. So it is difficult to create the layout of large amounts of wires in heavy-duty CNC machine tools.
The testing results for the above electrical temperature sensors show the discrete-point temperature of the heavy-duty CNC machine tool’s surface. The whole temperature field can be reconstructed by using the FDM. Due to the use of few discrete temperature points, it is difficult to establish an accurate integral temperature field of a heavy-duty CNC machine tool, particularly to calculate its internal temperature. Currently, prediction models such as multiple regression or neural networks, are all established based on discrete temperature points, so there is little research on the integral temperature field reconstruction of heavy-duty CNC machine tools. However, it is of great significance for the study of the thermal error mechanism to obtain the 3-D temperature field of CNC machine tools.
3.2 Non-Contact Type Temperature Measurement of Heavy-Duty CNC Machine Tools
Currently, infrared thermal imaging technology is a non-contact type temperature measurement method that is often applied to thermal error study of heavy-duty CNC machine tools, and it is part of the radiation temperature measurement method.
A thermal infrared imager gathers infrared radiant energy and delivered it to an infrared detector through the optical system, in order to process the infrared thermal image. Using the thermal infrared imager test results, one can select the key temperature points to establish a thermal error model. Qiu, et al. , measured the spindle box temperature field through FLIR thermal imager, and selected 18 temperature points symmetrically to establish the model of the spindle thermal components using the multiple linear regression method. Infrared thermal imaging is suitable for the study of the thermal characteristics of key parts of the heavy-duty CNC machine tools as it visualizes the global temperature field of the surface with a high temperature resolution.
The infrared thermal imager can visualize the temperature distribution of CNC machine tools, and plays an important role in thermal error study of CNC machine tools. However, the infrared thermal imager is a two-dimensional plane imaging infrared system. One infrared thermal imager cannot measure the overall global temperature field of heavy-duty CNC machine tools. Even with the use of multiple expensive infrared cameras for measuring the global temperature field of heavy-duty CNC machine tools, it is still difficult to track the temperature field of the moving parts when heavy-duty CNC machine tools are involved in actual processing.
The shortcomings mentioned in Section 3.1 and Section 3.2 limit the electrical temperature sensors and infrared sensing technology for monitoring the real-time temperature over the long-term in heavy-duty CNC machine tools. There must be some breakthroughs in the temperature field measurement of heavy-duty CNC machine tools in order to develop a highly intelligent temperature measurement and thermal error compensation system that is suitable for heavy-duty CNC machine tools for commercialization.
4.1 Thermal Error Monitoring of the Cutting Tool Tip
For the thermal error detecting of the cutting tool tip, three categories of sensors are mainly used, that are non-contact displacement detection sensors, high precision double ball gauge, and laser interferometer. The non-contact displacement detection sensors utilized in machine tools include eddy current transducers, capacitive transducers and laser displacement sensors. Though their sensing principles are different, their installation and error detection method are consistent with each other. The high precision double ball gauge and laser interferometer are mainly used to detect the dynamic geometric error of the machine tool, and they can also be competent at thermal error detecting.
4.1.1 Five-Point Detection Method
4.1.2 High Precision Double Ball Gauge Method
4.1.3 Laser Measurement Method
4.2 Thermal Deformation Monitoring of Large Structural Parts of the Machine Tool
5.1 Principle and Characteristics of Fiber Bragg Grating Sensors
A fiber Bragg grating sensor is a type of optical sensitive sensor that has been utilized and studied for nearly forty years. A fiber Bragg grating sensor has a number of unparalleled characteristics. It is small and explosion-proof, has electrical insulation, and is immune to electromagnetic interference. It offers high precision, and high reliability. Multiple FBG sensors can be arranged in one single fiber. Therefore, it has been widely used in many engineering fields and mechanical system .
A fiber Bragg grating sensor has a small volume, light weight, and high measurement precision. It is especially unparalleled when a series of FBG sensors that detect a variety of physical parameters distribute in a single fiber. It is suitable for heavy-duty CNC machine tool’s large volume, multiple heat sources, and complex structure.
A fiber Bragg grating sensor is highly resistant to corrosion, and high temperature. It is especially suitable for the processing under conditions of high temperature, high humidity, excessive vibration, dust, and other harsh environment. It meets the requirements of the long-term stability and reliability for machine tool detection.
A fiber Bragg grating sensor has electrical insulation, and is immune to electromagnetic interference (EMI), making it suitable for harsh processing conditions of the heavy-duty CNC machine tool. It can achieve accurate measurement of the thermal error of machine tools.
5.2 Temperature Field Monitoring of Heavy-Duty CNC Machine Tool Based on Fiber Bragg Grating Sensors
5.2.1 Fiber Bragg Grating Temperature Sensors for the Surface Temperature Measurement of Machine Tools
The fiber Bragg grating temperature measurement technology has become more mature, but the research in this field is mainly concentrated on the extremely high or low temperature measurement and the temperature sensitive enhancing technology. Currently, fiber Bragg grating temperature sensors can be divided into 5 parts by the form of packaging: tube-type fiber Bragg grating temperature sensor [83, 84], substrate-type fiber Bragg grating temperature sensor [85, 86], polymer packaged fiber Bragg grating temperature sensor , metal-coated fiber Bragg grating temperature sensor [88–93], and sensitization-type fiber Bragg grating temperature sensor .
When the temperature sensor’s surface makes contact with the machine tool, the heat flow will be more concentrated at the testing point. It results in temperature measurement error ΔT 1.
The thermal contact resistance between a temperature sensor’s surface and machine tool surface results in a temperature drop ΔT 2.
There is a certain distance between the temperature sensor’s sensing point and the surface of the machine tool, which creates the temperature measurement error ΔT 3.
Due to the existence of the coating layer on the surface of the fiber Bragg grating sensor, there is about a 0.15 mm gap between the machine tool surface and the fiber Bragg grating temperature sensing point. In the temperature gradient of −46.4 °C/mm, the small space is sufficient to produce a large temperature test error. By using thermal conductive paste, the uniformity of the surface temperature can be improved, and the error of the surface temperature measurement by FBG can be significantly reduced compared to that from a commercial thermal resistance surface temperature sensor. Ref.  studied influence of the installation types on surface temperature measurement by a FBG sensor. The surface temperature measurement error of the FBG sensor with single-ended fixation, double-ended fixation and fully-adhered fixation are theoretical analyzed and experimental studied. The single-ended fixation results in a positive linear error with increasing surface temperature, while the double-ended fixation and fully-adhered fixation both result in non-linear error with increasing surface temperature that are affected by thermal expansion strain of the tested surface’s material. Due to its linear error and strain-resistant characteristics, the single-ended fixation will play an important role in the FBG surface temperature sensor encapsulation design field .
5.2.2 Temperature Measurement of the Machine Tool Spindle Bearing Based on the Fiber Bragg Grating Sensors
The spindle is the core component with complex assembly mechanical structure in heavy-duty CNC machine tool. The spindle consists of the rotating shaft, the front and rear bearings, and the spindle base. For the motorized spindle, it also includes the rotor and stator. As the structure of the spindle is very compact and narrow, to fix the temperature sensor inside the spindle is difficult. The thermogenesis of spindle’s front bearings is a research hotspot that has great influence to the thermal error of the heavy-duty CNC machine tool.
5.2.3 Thermal Error Measurement of a Heavy-Duty CNC Machine Tool Based on the Fiber Bragg Grating Sensors
The fiber Bragg grating has the characteristics of multi-point temperature measurement. It can realize the layout of the temperature measurement points in the large surface area of the heavy-duty CNC machine tool, which can realize the reconstruction of the temperature field of the machine tool more accurately.
5.3 Heavy-Duty CNC Machine Tool Thermal Deformation Monitoring Based on Fiber Bragg Grating Sensors
There have been a number of achievements made in the application of the fiber Bragg grating strain sensor to large structural deformation measurements. By applying the classical beam theory, Kim and Cho  rearranged the formula to estimate the continuous deflection profile by using strains measured directly from several points equipped with the fiber Bragg sensor. Their method can be used to measure the deflection curve of bridges, which represents the global behavior of civil structures . Kang, et al. , investigated the dynamic structural displacements estimation using the displacement–strain relationship and measured the strain data using fiber Bragg grating. It is confirmed that the structural displacements can be estimated using strain data without displacement measurement. Kang, et al. , presented an integrated monitoring scheme for the maglev guideway deflection using wavelength-division-multiplexing (WDM) based fiber Bragg grating sensors, which can effectively avoid EMI in the maglev guideway. Yi, et al. , proposed a spatial shape reconstruction method using an orthogonal fiber Bragg grating sensor array.
The thermal error compensation technology of CNC machine tools has been developed over decades, but its successful application to commercial machine tools is limited. To some extent, it is still in the laboratory stage. Heavy-duty CNC machine tools play an important role in the national economic development and national defense modernization. However, due to the more complex thermal deformation mechanism and difficulty in the monitoring technology caused by a huge volume, overcoming its thermal error problems is extremely difficult.
The fiber Bragg grating sensing technology opens up a new areas of research for thermal error monitoring of heavy-duty CNC machine tools. We need to take advantage of the fiber Bragg grating sensing technology in global temperature fields and thermal deformation field measurements for heavy-duty CNC machine tool to study the thermal error mechanism of heavy-duty CNC machine tool. These can provide technological support for thermal structure optimization design of heavy-duty CNC machine tools. We also need to improve the thermal error prediction model, especially in regards to the robustness problem.
Intelligent manufacturing is an important trend in manufacturing technology, and the Industry 4.0 promises to create smart factory [111, 112]. Intelligent sensing technology is one of the indispensable foundations for the realization of intelligent manufacturing. The fusion of optical fiber sensing technology and high-end manufacturing technology is an important research direction that will play an important role in the Industry 4.0.
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