Dataframe loses level name after concat, only if columns types are str
#### Code Sample

```python
a = pd.DataFrame([1], index=[1], columns=['1'])
a.columns.names = ['n']
b = pd.DataFrame([1, 1], index=['1', '2'], columns=[1]).T
b.columns.names = ['n']
df1 = pd.concat([a, b])

a = pd.DataFrame([1], index=[1], columns=[1])
a.columns.names = ['n']
b = pd.DataFrame([1, 1], index=[1, 2], columns=[1]).T
b.columns.names = ['n']
df2 = pd.concat([a, b])

```
#### Problem description

When concatenating two dataframes with the same column level name (`'n'` in the case above), it is expected to find the same level name after the concatenation, i.e. on `df1`. This is not the case. If the columns are not `str`, as in `df2`, the behaviour is as expected. If this is not the expected behaviour, the two results should at least agree.

#### Expected Output

```
df1.columns.name == df2.columns.name
```

#### Output of ``pd.show_versions()``

<details>

commit: None
python: 3.7.3.final.0
python-bits: 64
OS: Windows
OS-release: 7
machine: AMD64
processor: Intel64 Family 6 Model 62 Stepping 4, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None
LOCALE: None.None

pandas: 0.24.2
pytest: None
pip: 19.1.1
setuptools: 41.0.1
Cython: None
numpy: 1.17.0rc1
scipy: None
pyarrow: None
xarray: None
IPython: None
sphinx: None
patsy: None
dateutil: 2.8.0
pytz: 2019.1
blosc: None
bottleneck: None
tables: None
numexpr: None
feather: None
matplotlib: None
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml.etree: None
bs4: None
html5lib: None
sqlalchemy: None
pymysql: None
psycopg2: None
jinja2: None
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None
gcsfs: None

</details>
