Laser beam profile – what is it?
Laser beam profiling is an essential tool for measuring and analyzing the properties of laser beams. In this article, we will explore the concept of laser beam profiling and explain the importance of understanding the characteristics of laser beams. We will discuss the various methods used to measure and analyze laser beams, including the use of cameras, sensors, and software, and explain the advantages and limitations of each approach. Additionally, we will look at the different applications of laser beam profiling, from laser system design and manufacturing to scientific research and medical applications. Whether you are new to the world of lasers or a seasoned professional, understanding laser beam profiling is essential for achieving optimal laser performance and unlocking the full potential of laser technology.
What is a laser beam profile?
A laser beam profile is a measurement of the intensity distribution of a laser beam at a particular point in space. The profile can be measured using a device called a laser beam profiler, which detects the light from the beam and creates a kind of a map of the intensity distribution in space. The profile of a laser beam can have different shapes, such as a Gaussian, Top-Hat, Lorentz or Bessel-like shape, depending on the characteristics of the laser and the optics used to shape the beam.
The image above presents an ideal, 2D Gaussian beam profile color using color map shown in the right part of the picture
The beam profile can also change over the distance, or along the beam propagation path, the most common example is beam divergence. The beam profile is important for many laser applications, as it determines the amount of energy delivered to a target, the size and shape of the laser’s focus spot, and the intensity and uniformity of the light at a given location
Using CMOS and CCD cameras to measure beam profile
Both CMOS (complementary metal-oxide-semiconductor) and CCD (charge-coupled device) cameras can be used to measure laser beam profiles. These cameras are able to detect the light from the laser beam and create an image of the intensity distribution, which can be analyzed to determine the beam profile.
Both CMOS and CCD cameras work by converting light into electrical charges. In a CMOS camera, each pixel in the sensor has its own photodetector and amplifier, which converts light into an electrical signal. The signals from all the pixels are then read out and processed to create an image. CMOS cameras have several advantages, including low power consumption, high readout speed, and the ability to integrate other functions, such as image processing, on the same chip.
A CCD camera, on the other hand, works by accumulating charges generated by incoming photons on a semiconductor and readout by shifting it from one register to another. CCD cameras have been traditionally known for their high image quality and low noise, but modern CMOS cameras have closed the gap.
Both camera types can be used to measure laser beam profiles, but they have different characteristics that may make one better suited to a particular application. For example, CCD cameras are known for their excellent sensitivity and low noise, which make them well-suited for low-light applications. CMOS cameras, on the other hand, are known for their high readout speeds and low power consumption, which make them well-suited for high-speed applications. They are said also to be more resistant to damage from too high laser powers.
In either case, the camera’s image needs to be captured by a software that can process the image of the laser spot and determine the beam profile. The most common one used is the Gaussian fit on the image intensity.
The example of the image of the surface of the CMOS array is shown in the picture below. This image was acquired using SEM (Scanning Electron Microscope) to investigate pixels’ geometry. Each small square shown in the picture is a real light-sensitive detector, a pixel.
3D intensity distribution is a laser beam profile
A laser beam profile can refer to the two-dimensional (2D) intensity distribution of a laser beam, or it can refer to the three-dimensional (3D) intensity distribution.
The 2D intensity distribution, also known as the transverse intensity distribution, is a measurement of the intensity of the laser beam at a particular point in space, such as at a focal point or a target. It shows how the intensity of the laser beam varies across the cross-sectional area of the beam.
The 3D intensity distribution, on the other hand, is a measurement of the intensity of the laser beam at multiple points in space and can provide a more complete picture of the beam’s characteristics. It describes how the intensity of the laser beam varies not only across the cross-sectional area but also along the beam’s axis, taking into account the beam divergence or focus point.
To measure 3D intensity distribution, a combination of methods can be used. For example, by measuring the intensity at multiple points in space by moving a sensor or the beam in a controlled manner, or by using a specialized imaging system, such as a Shack-Hartmann sensor or a scanning slit system. These methods can provide a more detailed and accurate characterization of the laser beam, which can be useful in applications such as laser material processing, where the 3D intensity distribution can affect the quality of the processed material.
Combining these images allows drawing “caustics” of the laser beam which is schematically shown in the picture below
Such a curve (caustics) allows e.g. to estimate one of the beam quality factors: M2.
Example artifacts in the laser beam profile
There are various types of artifacts that can be present in a laser beam profile, depending on the specific characteristics of the laser and the measurement system being used. Some examples of common artifacts include:
Noise:
This refers to any unwanted variations in the intensity of the laser beam, such as those caused by fluctuations in the power supply or temperature changes. Noise can make it difficult to accurately measure the beam profile and can appear as random variations in the intensity distribution.
Clipping:
This refers to the phenomenon of cutting off high intensity regions of the laser beam. It happens when the sensor used to measure the beam profile saturates, meaning it can’t detect the highest intensity regions of the beam. Clipping can lead to an underestimation of the true peak intensity of the beam.
Scattering:
This refers to the spreading of the beam due to the diffraction or reflection by any surfaces or materials in the beam path. Scattering can cause the beam to become distorted, leading to a change in the beam profile.
Spatial frequency dependent loss:
This can be caused by the optical components being not fully optimized for the laser wavelength and can lead to a non-uniform intensity distribution.
Mismatch of the reference beam:
This can occur in the Shack-Hartmann sensor, for example. The sensor uses a lenslet array to sample the laser beam and compare it to a reference beam. If the reference beam does not match the characteristics of the laser beam being measured, it can lead to inaccuracies in the measured beam profile.
Dust:
a very common problem in the laser systems is dust. It may appear on the optical elements. Then these small speckles may affect the laser beam quality causing diffraction on them but if the intensity of the beam increases the dust speckle may excessively absorb the radiation and transfer the heat to the mirror finally leading to its break.
It’s worth mentioning that Huaris Laser Cloud backed by the artificial intelligence detects dust in the beam fully automatically at the very early stage when the risk of damage of the optical components is low. It will warn the laser user and will advise cleaning the optical elements before they irreversibly get broken.
Diffraction:
There are various kinds of diffraction that can be observed with laser beams. E.g. linear or circular – depending on the structure that the laser beam has encountered on its propagation path. Also the beam may encounter rounded edges, like a mirror edge. Then the resulting diffraction pattern will have a roundish shape.
In similar fashion to the dust detection our AI can also detect various kinds of diffraction patterns appearing very early. Often even before the human eye can recognize that and it will give a clear indication that something is going wrong with the laser. In this case Huaris Cloud will also advise you maintenance actions, e.g. checking the beam alignment.
Example diffracted beam is shown in the picture below. In this case it is linear diffraction on the Gaussian beam presented in the Huaris profiling software local application.
It is worth noting that these artifacts might not appear in all the measurements, also a well-designed and calibrated system can reduce these artifacts considerably.
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